system

Abstract

We provide the system. [Solution] A means for selecting a template for notifying customers of various information based on customer information obtained from a database, A means for generating customized notification content based on the aforementioned template, A means of sending the generated notification content to the customer, A system that includes this.

Description

Technical Field

[0001] The technology of the present disclosure relates to a system.

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, the method including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In corporate business, it is difficult to provide customized notification content according to individual customers while improving communication efficiency with customers. In the conventional method, sales staff need to manually collect data of each customer and create emails individually, which takes time and effort. Also, due to manual creation, there may be variations in content, making it difficult to maintain customer satisfaction. Therefore, an object of the present invention is to automatically generate customized notification content for individual customers efficiently and improve business efficiency.

Means for Solving the Problems

[0005] The present invention provides the following means: a system including means for selecting a template for notifying a customer of various information based on customer information obtained from a database; means for generating customized notification content based on the template; and means for sending the generated notification content to the customer. In particular, the obtained customer information may include delivery status, schedule, and activation status, and the means for generating the notification content may include means for using artificial intelligence. Furthermore, the notification content is in email format, the system includes means for selecting a template based on conditions, and the means for obtaining customer information is performed via an API. In addition, the system includes means for recording a log of the transmission of the notification content. This streamlines communication with customers in corporate sales and enables the automatic provision of customized notification content tailored to individual customers.

[0006] A "database" is a system for storing, managing, and retrieving data.

[0007] "Customer information" refers to various information about a customer, specifically data including delivery status, schedule, and activation status.

[0008] A "template" is a pre-defined format for structuring the content of emails and notifications, serving as a foundation for customization according to specific circumstances.

[0009] "Customized notification content" refers to message content that is dynamically generated based on templates to suit specific customers or situations.

[0010] "Artificial intelligence" is a technology that imitates human intellectual activity and has functions such as data analysis, template selection, and automatic generation of notification content.

[0011] "Email format" refers to the standard format for sending and receiving electronic messages over the internet.

[0012] "Condition-based selection" is the process of dynamically choosing the appropriate template or method according to specific conditions or circumstances.

[0013] "API" is an abbreviation for Application Programming Interface, and it is a mechanism for different software programs to communicate with each other and exchange data.

[0014] A "transmission log" is a data file that stores records of notifications sent to customers, and includes information such as whether the transmission was successful or unsuccessful, and the time of transmission.

[0015] A "system" is a collection of devices or programs that execute a series of processes consisting of multiple interconnected components or means. [Brief explanation of the drawing]

[0016] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] It shows an emotion map on which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Embodiment 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Embodiment 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

Mode for Carrying Out the Invention

[0017] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0018] First, the terms used in the following description will be explained.

[0019] In the following embodiments, a processor with a reference numeral (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of a plurality of arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of a plurality of types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0020] In the following embodiments, a RAM (Random Access Memory) with a reference numeral is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0021] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0022] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0023] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0024] [First Embodiment]

[0025] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0026] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0027] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0028] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0029] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0030] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0031] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0032] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0034] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0035] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0036] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0037] System Embodiment

[0038] This invention relates to a system that streamlines customer notification operations in corporate sales and automatically generates and sends individually customized notification content. The system consists of the following main components:

[0039] Database for obtaining customer information

[0040] Means for selecting an appropriate template

[0041] Artificial intelligence for generating customized notification content

[0042] Means for sending notification content to customers

[0043] Program processing

[0044] 1. Data Acquisition

[0045] When a user needs to update information related to a specific customer, they send a request to the server via their terminal. The server retrieves the relevant customer information from the database, namely delivery status, schedule, and activation status. For example, to retrieve information for customer ID "12345", the server retrieves the relevant data from the database via a query.

[0046] 2. Template Selection

[0047] The server analyzes the acquired data and selects the template best suited to the customer's situation. For example, if delivery is delayed, a delay notification template is selected. Different templates are chosen depending on whether the delivery is on schedule or for other reasons.

[0048] 3. Generate customized emails

[0049] The server uses the AI ​​Writer extension to generate customized notification content based on the selected template and retrieved data. Specifically, it replaces placeholders in the template with dynamic data to generate individually customized email bodies.

[0050] 4. Send email

[0051] After reviewing the generated email content, the server sends the email to the customer's email address via the SMTP server. During sending, a transmission log is recorded, and information such as the success or failure of the transmission and the time of transmission is stored.

[0052] Specific example

[0053] Let's take the example of a case where delivery to customer "12345" is delayed. In this case, the process proceeds as follows:

[0054] 1. The terminal enters customer ID "12345" and sends a data retrieval request to the server.

[0055] 2. The server retrieves the delivery status, schedule, and activation status of the relevant customer from the database.

[0056] 3. The server analyzes the acquired data and, because a delivery delay has occurred, selects a delay notification template.

[0057] 4. The server generates customized notification content using AI Writer based on templates and data.

[0058] Example: "We sincerely apologize, but the delivery of product ID: 12345 is delayed. We will contact you later with the new delivery date."

[0059] 5. The server sends the generated email to "customer@example.com".

[0060] In this way, this system streamlines customer notification operations for corporate sales departments and enables the rapid delivery of customized notifications to individual customers.

[0061] The following describes the processing flow.

[0062] Step 1:

[0063] A user requests to view or send updated information about a specific customer via their device. The user uses a GUI to enter the relevant customer ID and triggers a data retrieval request.

[0064] Step 2:

[0065] The device sends the user's request to the server as an API request. The request includes the customer ID and the necessary information.

[0066] Step 3:

[0067] The server receives the request and sends a query to the database based on the specified customer ID. The server retrieves customer information, including delivery status, schedule, and activation status.

[0068] Step 4:

[0069] The server analyzes customer information retrieved from the database and selects a template appropriate to the situation. For example, if delivery is delayed, a delay notification template will be selected.

[0070] Step 5:

[0071] The server loads a selected template and generates customized notification content using an AI Writer extension based on customer information. The template's placeholders are replaced with dynamic data, creating individually customized email content.

[0072] Step 6:

[0073] The server passes the generated notification content to the SMTP server, which then sends an email to the customer's email address. The outgoing email contains dynamically generated customized content.

[0074] Step 7:

[0075] The server records email sending logs. It saves information such as whether the email was sent successfully or not, and the time of sending, to facilitate later review and troubleshooting.

[0076] Step 8:

[0077] Users can check the sending logs as needed to evaluate whether notifications were delivered successfully. The logs contain detailed records of the sending status of each email.

[0078] These steps enable the system to perform customer notification tasks efficiently and effectively, and to quickly deliver customized notifications to individual customers.

[0079] (Example 1)

[0080] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0081] In corporate sales, customer notification tasks require the rapid generation and efficient transmission of individually customized notification content. Traditional manual notification methods are time-consuming, labor-intensive, and prone to human error. Furthermore, selecting and customizing templates to suit diverse customer situations is difficult, making them unsuitable for today's business environment where quick and accurate responses are essential.

[0082] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0083] In this invention, the server includes means for obtaining specific customer information based on a request received from a device, means for obtaining customer information from a database using queries, means for analyzing the obtained customer information and selecting an appropriate template, means for generating customized notification content using an artificial intelligence model based on the selected template and obtained data, means for sending the generated notification content to the customer, and means for recording a transmission log. This makes it possible to automate customer notification operations and provide customized notification content quickly and accurately.

[0084] A "device" is an input device that sends a request to retrieve customer information to a server, or a device that has that function.

[0085] A "request" is data that a device sends to a server to request specific customer information.

[0086] A "server" is a central processing unit that acquires, analyzes, generates, and transmits customer information.

[0087] A "database" is a data storage system that manages and stores customer information.

[0088] A "query" is a command or question that is executed against a database to retrieve specific information.

[0089] "Customer information" refers to data related to a customer, including information such as shipping status, schedule, and connection status.

[0090] A "template" is a format for describing notification content, and it includes placeholders that are appropriate for specific situations.

[0091] An "artificial intelligence model" is an algorithm or program that uses machine learning or deep learning techniques to generate customized notification content.

[0092] "Notification content" refers to the message sent to the customer, generated based on a template and customer information.

[0093] "Transmission means" refers to the means of communication used to send the generated notification content to the customer.

[0094] A "transmission log" records data such as the success or failure of sending notification content, and the time of transmission.

[0095] System Embodiment

[0096] This invention relates to a system that streamlines customer notification operations in corporate sales and automatically generates and sends individually customized notification content. The system consists of the following main components:

[0097] Database for obtaining customer information

[0098] Means for selecting an appropriate template

[0099] Artificial intelligence model for generating customized notification content

[0100] Means for sending notification content to customers

[0101] Program processing

[0102] Data acquisition

[0103] When a user needs to update information related to a specific customer, they send a request to the server via their terminal. The server retrieves the relevant customer information from the database. For example, to retrieve information for customer ID "12345", the server executes an SQL query to obtain the customer's delivery status, schedule, and connection status.

[0104] Template Selection

[0105] The server analyzes the acquired data and selects the template best suited to the customer's situation. For example, if delivery is delayed, a delay notification template will be selected. Different templates are selected depending on whether the delivery is on schedule or for other reasons.

[0106] Custom email generation

[0107] Based on the selected template and acquired data, the server uses an artificial intelligence model (e.g., OpenAI®'s GPT-3®) to generate customized notification content. Specifically, it replaces placeholders in the template with dynamic data to generate individually customized email bodies.

[0108] Examples of prompt statements are as follows:

[0109] "Please use the following template to generate a customized email regarding a delivery delay for customer ID "12345". Template: Dear {{customer_name}}, We hope this email finds you well. The delivery of product ID: {{product_id}} is delayed. We will contact you later with the new delivery date. Customer data: { "customer_name": "Taro Yamada", "product_id": "XYZ123"}"

[0110] Send email

[0111] After reviewing the generated email content, the server sends the email to the customer's email address via an SMTP server (e.g., Postfix). During sending, a transmission log is recorded, and information such as success or failure of transmission and the time of transmission is stored.

[0112] Specific example

[0113] Let's take the example of a case where the delivery for customer ID "12345" is delayed. In this case, the process proceeds as follows:

[0114] 1. The user enters customer ID "12345" on their terminal and sends a data retrieval request to the server.

[0115] 2. The server retrieves the delivery status, schedule, and connection status of the relevant customer from the database.

[0116] 3. The server analyzes the acquired data and, because a delivery delay has occurred, selects a delay notification template.

[0117] 4. The server generates customized notification content using an AI model based on templates and data.

[0118] Example: "We sincerely apologize, but the delivery of product ID: 12345 is delayed. We will contact you later with the new delivery date."

[0119] 5. The server sends the generated email to the customer's email address.

[0120] In this way, this system streamlines customer notification operations for corporate sales departments and enables the rapid delivery of customized notifications to individual customers.

[0121] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0122] Step 1:

[0123] The user enters a customer information update request on their terminal. This includes entering the customer ID (e.g., 12345) and other necessary information into the input form. When the user clicks the "Submit" button, the information is sent to the server as an HTTP request.

[0124] Input: Customer ID, Request Details

[0125] Output: Sending requested data

[0126] Step 2:

[0127] The server parses the received request data. The server extracts the customer ID from the request data, generates an SQL query to retrieve the corresponding customer information from the database (for example, MySQL®), and executes it. A specific query might be "SELECT FROM customers WHERE customer_id = '12345'" and retrieves the results.

[0128] Input: Request data (Customer ID)

[0129] Output: Retrieval of customer information data

[0130] Step 3:

[0131] The server analyzes the acquired customer information data. This analysis is performed using, for example, the Pandas library. The server analyzes information such as the customer's delivery status, schedule, and connection status to determine which template is appropriate. Based on this information, it selects the appropriate template (for example, a delay notification template).

[0132] Input: Customer information data

[0133] Output: Selected template

[0134] Step 4:

[0135] The server uses the selected template and analyzed customer information to send a prompt to a generating AI model (e.g., OpenAI's GPT-3) to generate customized notification content. A prompt might include, "Please use the following template to generate a customized email for when the delivery of customer ID "12345" is delayed." The AI ​​model then generates specific notification content (e.g., "Mr. / Ms. Yamada, we sincerely apologize, but the delivery of product ID: 12345 is delayed.").

[0136] Input: Selected template, customer information

[0137] Output: Customized notification content

[0138] Step 5:

[0139] The server sends the generated notification content to the customer's email address via an SMTP server (e.g., Postfix). The server establishes an SMTP connection and sends the notification content to the customer's email address according to the email sending protocol. After sending is complete, the server records information such as success / failure and sending time in the sending log.

[0140] Input: Customized notification content, customer's email address

[0141] Output: Transmission results, transmission log recording

[0142] By following these steps, this system can quickly and accurately generate and send customized customer notification content.

[0143] (Application Example 1)

[0144] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0145] In today's food delivery industry, the various notification tasks for customers are extremely diverse and difficult to perform efficiently. While it is necessary to quickly notify each customer of their delivery status, estimated arrival time, and delivery person information, customizing the content of these notifications individually is time-consuming. Furthermore, delays in selecting appropriate templates for situations such as delivery delays or special offers can lead to decreased customer satisfaction and reduced operational efficiency.

[0146] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0147] In this invention, the server includes means for selecting a template for notifying customers of various information based on customer information obtained from a database, means for generating customized notification content based on the template, communication means for sending the generated notification content to the customer, and means for sending the notification content in push notification format on various devices. This makes it possible to quickly generate and send individually customized notification content.

[0148] A "database" is an electronic system for systematically organizing information and efficiently searching, updating, and managing it.

[0149] "Customer information" refers to data about the customer, including name, contact information, delivery status, estimated arrival time, and delivery person information.

[0150] A "template" is a document model with a specific format and structure, and serves as a basic framework for automatically generating notification content.

[0151] "Customized notification content" refers to notification messages that are individually tailored based on the specific circumstances and information of a particular customer.

[0152] "Means of generation" refers to devices or programs that have the ability or function to perform a specific process and produce a desired output result.

[0153] "Communication methods" refer to means of sending information to specific recipients, and include email and push notifications.

[0154] "Push notifications" are a notification format that sends information to the user in real time and displays it immediately on the device screen.

[0155] "Delivery status" refers to status information that indicates the stage of delivery for an ordered item in a food delivery service.

[0156] "Estimated arrival time" refers to information indicating the time when a particular delivery is expected to arrive at the designated recipient's location.

[0157] "Delivery driver information" refers to information about the employee responsible for delivery, including their name, contact information, and delivery history.

[0158] A "generative AI model" is an algorithm or data model that uses artificial intelligence to process data and generate output tailored to a specific task or purpose.

[0159] The system for realizing this invention automatically generates and sends individually customized notification content based on customer information obtained from a database. This system consists of the following main components.

[0160] System components

[0161] 1. Database

[0162] A database is an electronic system for systematically organizing customer information and efficiently searching, updating, and managing it. Specifically, it stores customer delivery status, estimated arrival time, and delivery person information.

[0163] 2. Server

[0164] The server retrieves customer information from the database, analyzes that information, and selects the optimal template. Furthermore, it uses a generative AI model to generate customized notification content based on the selected template.

[0165] 3. Means of communication

[0166] The server has communication means to send the generated notification content to various devices. This includes email and push notifications.

[0167] 4. Terminal

[0168] The terminals are devices used by customers and delivery personnel, and include smartphones and tablets. These terminals display information sent as push notifications in real time.

[0169] Program processing

[0170] The server runs using programs such as Python and Flask. It uses sqlite3 for database connections and smtplib for sending emails. OpenAI GPT-3 is used for the generative AI model.

[0171] First, the user sends a request from their device to the server to review or update information related to a specific customer. The server retrieves the customer information from the database, analyzes it, and selects an appropriate notification template. Next, it uses a generative AI model to generate customized notification content based on the template. This notification content includes information such as the customer name, order ID, scheduled arrival time, and new estimated arrival time.

[0172] The generated notification content is sent to various devices via communication means. For example, if it is sent as a push notification to a smartphone, the customer can immediately check the delivery status. The sent notification log is recorded, and information such as the success or failure of the transmission and the time of transmission is stored.

[0173] Specific example

[0174] Here are some specific examples of how customers use food delivery services.

[0175] 1. The user sends a request from their device to the server to check the delivery status.

[0176] 2. The server retrieves the relevant customer information from the database and recognizes that a delivery delay has occurred.

[0177] 3. The server selects a delayed notification template and uses a generation AI model to generate customized notification content.

[0178] 4. The generated notification reads: "We sincerely apologize, but the delivery of your ordered item ID: ABC123 is delayed. The new estimated arrival time is 14:30."

[0179] 5. This notification content will be sent to the smartphone as a push notification via a communication method.

[0180] Example of a prompt

[0181] "Use the generation AI model to generate a delivery delay notification for customer 'Yamada Taro' with order ID 'XYZ789'. The estimated arrival time is '15:00'."

[0182] In this way, the present invention is a system that can streamline customer notification operations in the food delivery industry and improve customer satisfaction.

[0183] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0184] Step 1:

[0185] The user uses a terminal to check or update the delivery status and sends a request to the server. The input is the customer ID and the type of information to be checked, and the output is the request data sent to the server. Once the request is sent, the server receives the data and proceeds to the next step.

[0186] Step 2:

[0187] The server queries the database based on the received request. The input is the customer ID and related request information, and the output is data retrieved from the database, such as the customer's delivery status, estimated arrival time, and delivery person information. The server retrieves the relevant data from the database and prepares it for analysis.

[0188] Step 3:

[0189] The server analyzes the retrieved customer information and selects a template appropriate to the customer's situation. The input is customer information retrieved from the database, and the output is the selected template. For example, if a delivery is delayed, the delay notification template will be selected.

[0190] Step 4:

[0191] The server generates customized notification content using a generative AI model based on the selected template and retrieved data. The input is the template and customer information, and the output is a specific notification message. Specifically, the AI ​​model inserts the customer's specific data into placeholders within the template to generate the final notification content.

[0192] Step 5:

[0193] The server reviews the generated notification content and sends it to the customer via a communication method. The input is the generated notification message, and the output is the notification sent to various devices. Specifically, the server either sends an email using an SMTP server or sends a real-time notification to a smartphone using a push notification system.

[0194] Step 6:

[0195] The server logs sent notifications, saving information such as success, failure, and transmission time. Input is the status information of the transmission result, and output is the transmission history stored in log files or a database. This enables troubleshooting and history auditing.

[0196] This entire processing step allows users to track the delivery status in real time and receive personalized notifications quickly.

[0197] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0198] System Embodiment

[0199] This invention relates to a system that streamlines customer communication in corporate sales, automatically generates customized notification content, and further customizes it based on user sentiment. The main components of the system include the following:

[0200] database

[0201] Template selection method

[0202] Artificial intelligence that generates customized notification content

[0203] Means of sending notification content to customers

[0204] Emotional Engine

[0205] Program processing

[0206] 1. User requests and data acquisition

[0207] A user requests updates regarding specific customer information via their device. The user enters the customer ID and sends a data retrieval request to the server. The server retrieves the customer information from the database. This information includes delivery status, schedule, and activation status.

[0208] 2. Emotion recognition

[0209] The device sends the user's facial expressions, voice, or text input to the emotion engine. The emotion engine analyzes this data to recognize the user's emotions. For example, if it determines that the user is feeling anxious, it customizes the notification content based on that information.

[0210] 3. Template Selection

[0211] The server analyzes the acquired customer information and sentiment data obtained from the sentiment engine, and selects an appropriate template based on this analysis. For example, if the sentiment engine determines that the user is anxious, it will select a template that provides a greater sense of reassurance.

[0212] 4. Generating customized emails

[0213] The server uses the AI ​​Writer extension to generate customized notification content based on the selected template, acquired data, and sentiment data. Specifically, it replaces placeholders within the template with dynamic data and sentiment-based content.

[0214] 5. Send email

[0215] The server sends the generated customized notification content to the customer using an SMTP server. After the transmission is complete, a transmission log is recorded for later review.

[0216] Specific example

[0217] Let's take the example of how to handle a situation where a delivery to customer "12345" is delayed, and the user is feeling anxious about this situation.

[0218] 1. The terminal enters customer ID "12345" and sends a data retrieval request to the server.

[0219] 2. The server retrieves customer delivery status, schedule, and activation status from the database.

[0220] 3. Simultaneously, the device transmits the user's facial expressions and voice to the emotion engine, which recognizes that the user is feeling anxious.

[0221] 4. The server analyzes the acquired data and sentiment data, selects a "delayed notification template," and then adds "content that provides a sense of relief."

[0222] 5. The server uses an AI Writer to generate customized notification content.

[0223] Example: "Customer, there is a delay in the delivery of product ID: 12345. We will contact you shortly with the new delivery date. We apologize for any inconvenience this may cause. Please contact us if you have any questions or concerns."

[0224] 6. The server sends the generated email to the customer "customer@example.com" and records the sending log.

[0225] These processes enable efficient customer notifications and allow for customization based on user emotions, which is expected to improve operational efficiency and customer satisfaction.

[0226] The following describes the processing flow.

[0227] Step 1:

[0228] The user requests an update to customer information via their device. Specifically, the user enters a specific customer ID in the GUI and clicks the "Get Data" button.

[0229] Step 2:

[0230] The device sends the user's request to the server as an API request. The request includes the specified customer ID.

[0231] Step 3:

[0232] The server receives the API request and sends a query to the database based on the specified customer ID. For example, it retrieves the delivery status, schedule, and activation status for customer ID "12345".

[0233] Step 4:

[0234] The server analyzes customer information retrieved from the database. For example, it checks whether deliveries are delayed or whether the schedule is on track.

[0235] Step 5:

[0236] The device collects data to recognize the user's emotions. Specifically, it captures facial expressions with the device's camera, collects voice tone with the microphone, and analyzes text input.

[0237] Step 6:

[0238] The device sends collected emotional data to the emotion engine. The emotion engine analyzes this data and recognizes the user's emotions. For example, it might determine that the user is feeling anxious.

[0239] Step 7:

[0240] The server selects a template based on customer information and sentiment data it has acquired. If delivery is delayed, it selects a delay notification template, and if the user is feeling anxious, it selects a template that includes content to provide reassurance.

[0241] Step 8:

[0242] The server loads a selected template and uses the AI ​​Writer extension to customize the notification content. For example, it generates emails that include messages such as "Delivery is delayed," "New deadline announcement," and "Message to alleviate concerns."

[0243] Step 9:

[0244] The server verifies the generated customized email content and sends it to the customer's email address via the SMTP server. For example, it sends an email to "customer@example.com".

[0245] Step 10:

[0246] The server records transmission logs. It saves information such as whether the transmission was successful or unsuccessful, and the transmission time, so that it can be reviewed later.

[0247] Step 11:

[0248] Users can check the sending logs as needed to evaluate whether notifications were delivered successfully. The logs contain detailed records of the sending status of each email.

[0249] In this way, the system efficiently performs a series of processes, from acquiring customer information to generating customized notification content, analyzing sentiment data, and sending emails, enabling it to respond in a way that takes user emotions into consideration.

[0250] (Example 2)

[0251] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0252] In modern corporate sales, it is crucial to streamline communication with customers while generating customized notifications tailored to individual customer needs. However, while traditional systems could generate automated notifications based on customer information, they did not further customize the notification content to consider user emotions. As a result, customers received standardized messages, and it was difficult to respond in a way that took individual circumstances and emotions into account. Furthermore, the manual process of selecting templates and customizing notification content was also inefficient.

[0253] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for selecting a template for notifying customers of various information based on customer information obtained from a database, means for analyzing the obtained customer information and user sentiment data to select the optimal template, means for using artificial intelligence to generate customized notification content based on the selected template, and means for sending the generated notification content to the customer. This makes it possible to generate more personalized notification content based on the user's sentiment, thereby improving customer satisfaction. Furthermore, automated template selection and notification content generation can improve operational efficiency.

[0254] A "database" is a computer system that systematically stores information and data, making it searchable and retrievable.

[0255] "Customer information" refers to data about a customer, including information such as delivery status, schedule, and activation status.

[0256] A "template" is a pre-configured document or format tailored to a specific purpose, and it forms the basis of the notification content.

[0257] "User emotion data" refers to data related to emotions analyzed from the user's facial expressions, voice, or text input.

[0258] "Analysis" is the process of examining data and information in detail to find patterns, trends, and relationships within them.

[0259] "Artificial intelligence" is a technology that enables machines to learn, make decisions, and solve problems like humans, and in this invention, it is used to generate customized notification content.

[0260] "Notification content" refers to the information and messages that should be conveyed to the customer, and is customized based on templates and sentiment data.

[0261] "Transmission" refers to the act of delivering information or data to another system or user through a computer system.

[0262] The system of this invention is designed to streamline communication with customers in corporate sales and to automatically generate and send customized notification content based on the user's emotions to the customer. The main components of the system include a database, a template selection means, artificial intelligence for generating customized notification content, means for sending the notification content to the customer, and an emotion engine.

[0263] Specific processing of the program

[0264] The system processes are structured as follows:

[0265] 1. User requests and data acquisition

[0266] A user requests updates regarding specific customer information via their device. The user enters the customer ID into the device and sends a data retrieval request to the server. The server retrieves the relevant customer information (delivery status, schedule, activation status, etc.) from the database.

[0267] 2. Emotion recognition

[0268] The device transmits the user's facial expressions, voice, and text input to the emotion engine in real time. The emotion engine analyzes this data and recognizes the emotions the user is feeling (e.g., anxiety, joy). This emotion data is sent to a server and stored there.

[0269] 3. Template Selection

[0270] The server analyzes the acquired customer information and sentiment data to select a notification template. The server uses rule-based algorithms or machine learning models to choose the best one from several pre-configured email templates.

[0271] 4. Generating customized emails

[0272] The server uses its AI Writer function to generate customized notification content based on the selected template, acquired data, and sentiment data. Specifically, it replaces placeholders within the template with dynamic data and sentiment-based content.

[0273] 5. Send email

[0274] The server uses an SMTP server to send the generated customized notification content to the specified customer email address. After sending, the server records the sending result and saves it to a log file or database for later review.

[0275] Hardware and software to be used

[0276] Database: A database system for storing and managing customer information (delivery status, schedule, activation status, etc.).

[0277] Template selection method: Program logic or algorithm executed within the server.

[0278] Artificial intelligence: AI modules for generating customized notification content (e.g., AI Writer).

[0279] Emotion Engine: A software module equipped with facial recognition and speech analysis capabilities.

[0280] SMTP server: A mail sending server used to send notification content to customers.

[0281] Specific example

[0282] If the delivery of a certain customer "12345" is delayed and the user feels uneasy about this situation, the following processing will be shown.

[0283] 1. User requirements and data acquisition

[0284] The user enters the customer ID "12345" into the terminal and sends a data acquisition request to the server.

[0285] The server acquires the delivery status, schedule, and activation status of the customer from the database.

[0286] 2. Emotion recognition

[0287] The terminal sends the user's expression and voice to the emotion engine, and the emotion engine recognizes that the user is feeling uneasy.

[0288] 3. Template selection

[0289] The server analyzes the acquired data and emotion data, selects the "delay notification template", and further adds "content to give a sense of relief".

[0290] 4. Customized email generation

[0291] The server uses an AI Writer to generate customized notification content.

[0292] Example: "Dear customer, the delivery of merchandise ID: 12345 has been delayed. We will contact you shortly regarding the new delivery date. We apologize for any inconvenience caused. If you notice anything, please contact us."

[0293] 5. Email sending

[0294] The server sends the generated email to the customer "customer@example.com" and records the sending log.

[0295] Example of a prompt

[0296] Prompt: "Generate a customized email to reassure a customer whose delivery is delayed. The customer ID is 12345."

[0297] Expected output example:

[0298] "Dear customer, there is a delay in the delivery of product ID: 12345. We will contact you shortly with the new delivery date. We apologize for any inconvenience this may cause. Please contact us if you have any questions or concerns."

[0299] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0300] Processing flow

[0301] Step 1:

[0302] A user requests updates regarding specific customer information via their device. Specifically, the user logs into the device, enters the customer ID, and clicks the "Get Data" button. This action causes the device to send a data retrieval request, including the customer ID, to the server. The input is the customer ID, and the output is a request message containing the data retrieval request. The server receives the request and creates and executes a database query.

[0303] Step 2:

[0304] The server queries the database to retrieve customer information. This process uses the customer ID submitted as input to retrieve information such as the customer's delivery status, schedule, and activation status from the database. Specifically, an SQL query like "SELECT FROM customer_information WHERE customer_ID = '12345'" is executed. The output is a customer_information dataset as the query result.

[0305] Step 3:

[0306] The terminal captures the user's expression, voice, and text input in real time. The terminal sends the captured data to the emotion engine, and the emotion engine analyzes it to generate the user's emotion data. The input is the user's face image or voice data, and the data is processed by an expression recognition algorithm or a voice analysis algorithm. The output is the analyzed emotion data (e.g., anxiety, joy, etc.).

[0307] Step 4:

[0308] Based on the obtained customer information and emotion data, the server selects the optimal template. The server selects an appropriate template from the template storage using a rule-based algorithm or a machine learning model. The input is the obtained customer information and emotion data, and the output is the selected notification template. For example, when the customer's delivery is delayed and the user is feeling anxious, the "Delay Notification Template" is selected.

[0309] Step 5:

[0310] The server generates customized notification content based on the selected template, the obtained data, and the emotion data. Specifically, the AI's Writer function replaces the placeholders in the template with dynamic data or content according to the emotion. The input is the selected template, customer information, and emotion data, and the output is the generated customized notification content. For example, an email like "Dear customer, the delivery of product ID: 12345 is delayed. We will contact you soon regarding the new delivery date. We apologize for any inconvenience caused. If you notice anything, please contact us." is generated.

[0311] Step 6:

[0312] The server sends the generated customized notification content to the specified customer email address using an SMTP server. The inputs are the generated notification content and the customer's email address, and the output is the sent email and its result. This process includes connecting to the SMTP server, establishing an email sending session, sending the email content, and recording the sending log. After sending is complete, the sending log is recorded on the server for later review.

[0313] This allows the system to efficiently notify customers and provide customized notification content that takes user emotions into consideration.

[0314] (Application Example 2)

[0315] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0316] Conventional customer information notification systems have difficulty accurately reflecting customers' real-time emotions and intentions in their communication, resulting in problems such as decreased customer satisfaction and reduced sales efficiency. Furthermore, notification content based on standard templates lacks individualized attention to customers, potentially leading to missed business opportunities.

[0317] In Application Example 2, the specific processing performed by the specific processing unit 290 of the data processing device 12 is realized by the following means. In this invention, the server includes means for selecting a template for notifying customers of various information based on customer information obtained from a database, means for generating customized notification content based on the template, means for sending the generated notification content to the customer, and means for analyzing the user's emotions using an emotion recognition device and further customizing the notification content based on the results. This enables highly accurate customer service in real time, improving customer satisfaction and sales efficiency.

[0318] A "database" is an information management system that stores customer information and allows it to be searched and retrieved as needed.

[0319] A "template selection mechanism" is a means that has the function of automatically selecting an appropriate notification template based on customer information.

[0320] "Means for generating customized notification content" refers to methods for creating individually tailored notification content based on selected templates and customer data.

[0321] "Means for sending notification content to customers" refers to means that have the function of sending the generated notification content to customers.

[0322] An "emotion recognition device" is a device or software that analyzes a user's emotions from their facial expressions, voice, etc., and recognizes a specific emotional state.

[0323] "Visit history" refers to information about a customer's history of visiting a store, including the date, time, and frequency of visits.

[0324] "Purchase history" refers to a record of information about products and services that a customer has purchased in the past.

[0325] "Facial expression" refers to the emotional state indicated by the movement of a customer's facial muscles.

[0326] "Voice" refers to an audio signal used to recognize an emotional state by analyzing the customer's voice characteristics, such as tone, pitch, and speed.

[0327] "Artificial intelligence" refers to computer algorithms or software that learn from large amounts of data and automatically perform specific tasks.

[0328] A "generative AI model" is a model that uses artificial intelligence technology to automatically generate content from input data.

[0329] "Real-time" refers to a state where processing and responses occur almost immediately after an event takes place, with virtually no delay.

[0330] A description of an embodiment for carrying out this invention will be provided. This system performs customer information acquisition, sentiment recognition, template selection, customized notification generation, and notification transmission in a series of steps.

[0331] Hardware and software to be used

[0332] hardware

[0333] Smartphones: Used by store staff, they function as input devices for acquiring customer information and recognizing emotions.

[0334] Server: The central hardware that performs data processing and runs AI models.

[0335] software

[0336] Database: Stores and manages customer information (visit history, purchase history, etc.).

[0337] EmotionEngine: Software that analyzes and recognizes emotions from the user's facial expressions and voice.

[0338] TemplateSelector: Software that selects the appropriate template based on customer information and sentiment data.

[0339] AIWriter: An artificial intelligence model that generates customized notification content based on analysis results.

[0340] SMTP server: A mail server used to send generated notification content to customers.

[0341] Data processing and data calculation workflow

[0342] 1. Data Acquisition

[0343] The server retrieves customer information (visit history, purchase history, etc.) from the database. The user (employee) enters the customer ID into their smartphone and sends a data retrieval request to the server. The server accesses the database and retrieves the necessary information.

[0344] 2. Emotion recognition

[0345] Users interact with customers via their smartphones and capture their facial expressions with the camera. The smartphones send this data to an emotion recognition device called EmotionEngine, which analyzes and recognizes emotional data. For example, it can identify emotions such as "dissatisfaction" or "reassurance" from facial expressions and tone of voice.

[0346] 3. Template Selection

[0347] The server uses TemplateSelector to choose an appropriate template based on the acquired customer information and analyzed sentiment data. This template is the basic text for efficiently structuring notification content.

[0348] 4. Generate customized notifications

[0349] The server uses AIWriter to customize the selected template based on customer information and sentiment data. The generated notification content is tailored to each customer.

[0350] 5. Send Notification

[0351] The server sends the generated customized notification content to the customer using an SMTP server. After sending, a transmission log is recorded for later review.

[0352] Specific example

[0353] scenario

[0354] Customer "Customer ID: 54321" enters the store. A store employee uses a smartphone app to retrieve customer information. Based on the customer's facial expression, it is determined that the customer is dissatisfied with the waiting time.

[0355] Prompts for Generative AI Models

[0356] Please retrieve the information for customer ID: 54321.

[0357] We recognized that the customer was dissatisfied.

[0358] Choose an appropriate template and create a customized notification that includes reassuring content.

[0359] This will allow for more efficient and effective customer service in physical stores, leading to improved customer satisfaction and increased operational efficiency.

[0360] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0361] Step 1:

[0362] The user enters their customer ID using their smartphone and sends a data retrieval request to the server. The server retrieves customer information corresponding to the entered customer ID from the database and responds. The input is the customer ID, and the output is the corresponding customer information (visit history, purchase history, etc.).

[0363] Step 2:

[0364] The terminal interacts with the customer and captures their facial expressions using its camera, sending the collected data to the EmotionEngine, an emotion recognition device. The EmotionEngine analyzes this data and outputs the customer's emotional data (e.g., dissatisfaction, relief, etc.). The input is emotional input data such as facial expressions and voice, and the output is the recognized emotional data.

[0365] Step 3:

[0366] The server uses TemplateSelector to choose the optimal template based on the acquired customer information and emotion data from EmotionEngine. In this process, the server determines the template considering the customer's state and emotions. The input is customer information and emotion data, and the output is the selected template.

[0367] Step 4:

[0368] The server sends the selected template, retrieved customer information, and sentiment data to the AIWriter to generate customized notification content. The AIWriter uses this information to replace the template's placeholders with dynamic data and sentiment-based content. The inputs are the template, customer information, and sentiment data, while the output is the customized notification content.

[0369] Step 5:

[0370] The server sends the generated customized notification content to the customer using the SMTP server. After the email is delivered to the customer via the SMTP server, a transmission log is recorded for later review. The input is the customized notification content, and the output is the transmission log and delivery to the customer.

[0371] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0372] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0373] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0374] [Second Embodiment]

[0375] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0376] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0377] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0378] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0379] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0380] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0381] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0382] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0383] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0384] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0385] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0386] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0387] System Embodiment

[0388] This invention relates to a system that streamlines customer notification operations in corporate sales and automatically generates and sends individually customized notification content. The system consists of the following main components:

[0389] Database for obtaining customer information

[0390] Means for selecting an appropriate template

[0391] Artificial intelligence for generating customized notification content

[0392] Means for sending notification content to customers

[0393] Program processing

[0394] 1. Data Acquisition

[0395] When a user needs to update information related to a specific customer, they send a request to the server via their terminal. The server retrieves the relevant customer information from the database, namely delivery status, schedule, and activation status. For example, to retrieve information for customer ID "12345", the server retrieves the relevant data from the database via a query.

[0396] 2. Template Selection

[0397] The server analyzes the acquired data and selects the template best suited to the customer's situation. For example, if delivery is delayed, a delay notification template is selected. Different templates are chosen depending on whether the delivery is on schedule or for other reasons.

[0398] 3. Generate customized emails

[0399] The server uses the AI ​​Writer extension to generate customized notification content based on the selected template and retrieved data. Specifically, it replaces placeholders in the template with dynamic data to generate individually customized email bodies.

[0400] 4. Send email

[0401] After reviewing the generated email content, the server sends the email to the customer's email address via the SMTP server. During sending, a transmission log is recorded, and information such as the success or failure of the transmission and the time of transmission is stored.

[0402] Specific example

[0403] Let's take the example of a case where delivery to customer "12345" is delayed. In this case, the process proceeds as follows:

[0404] 1. The terminal enters customer ID "12345" and sends a data retrieval request to the server.

[0405] 2. The server retrieves the delivery status, schedule, and activation status of the relevant customer from the database.

[0406] 3. The server analyzes the acquired data and, because a delivery delay has occurred, selects a delay notification template.

[0407] 4. The server generates customized notification content using AI Writer based on templates and data.

[0408] Example: "We sincerely apologize, but the delivery of product ID: 12345 is delayed. We will contact you later with the new delivery date."

[0409] 5. The server sends the generated email to "customer@example.com".

[0410] In this way, this system streamlines customer notification operations for corporate sales departments and enables the rapid delivery of customized notifications to individual customers.

[0411] The following describes the processing flow.

[0412] Step 1:

[0413] A user requests to view or send updated information about a specific customer via their device. The user uses a GUI to enter the relevant customer ID and triggers a data retrieval request.

[0414] Step 2:

[0415] The device sends the user's request to the server as an API request. The request includes the customer ID and the necessary information.

[0416] Step 3:

[0417] The server receives the request and sends a query to the database based on the specified customer ID. The server retrieves customer information, including delivery status, schedule, and activation status.

[0418] Step 4:

[0419] The server analyzes customer information retrieved from the database and selects a template appropriate to the situation. For example, if delivery is delayed, a delay notification template will be selected.

[0420] Step 5:

[0421] The server loads a selected template and generates customized notification content using an AI Writer extension based on customer information. The template's placeholders are replaced with dynamic data, creating individually customized email content.

[0422] Step 6:

[0423] The server passes the generated notification content to the SMTP server, which then sends an email to the customer's email address. The outgoing email contains dynamically generated customized content.

[0424] Step 7:

[0425] The server records email sending logs. It saves information such as whether the email was sent successfully or not, and the time of sending, to facilitate later review and troubleshooting.

[0426] Step 8:

[0427] Users can check the sending logs as needed to evaluate whether notifications were delivered successfully. The logs contain detailed records of the sending status of each email.

[0428] These steps enable the system to perform customer notification tasks efficiently and effectively, and to quickly deliver customized notifications to individual customers.

[0429] (Example 1)

[0430] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0431] In corporate sales, customer notification tasks require the rapid generation and efficient transmission of individually customized notification content. Traditional manual notification methods are time-consuming, labor-intensive, and prone to human error. Furthermore, selecting and customizing templates to suit diverse customer situations is difficult, making them unsuitable for today's business environment where quick and accurate responses are essential.

[0432] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0433] In this invention, the server includes means for obtaining specific customer information based on a request received from a device, means for obtaining customer information from a database using queries, means for analyzing the obtained customer information and selecting an appropriate template, means for generating customized notification content using an artificial intelligence model based on the selected template and obtained data, means for sending the generated notification content to the customer, and means for recording a transmission log. This makes it possible to automate customer notification operations and provide customized notification content quickly and accurately.

[0434] A "device" is an input device that sends a request to retrieve customer information to a server, or a device that has that function.

[0435] A "request" is data that a device sends to a server to request specific customer information.

[0436] A "server" is a central processing unit that acquires, analyzes, generates, and transmits customer information.

[0437] A "database" is a data storage system that manages and stores customer information.

[0438] A "query" is a command or question that is executed against a database to retrieve specific information.

[0439] "Customer information" refers to data related to a customer, including information such as shipping status, schedule, and connection status.

[0440] A "template" is a format for describing notification content, and it includes placeholders that are appropriate for specific situations.

[0441] An "artificial intelligence model" is an algorithm or program that uses machine learning or deep learning techniques to generate customized notification content.

[0442] "Notification content" refers to the message sent to the customer, generated based on a template and customer information.

[0443] "Transmission means" refers to the means of communication used to send the generated notification content to the customer.

[0444] A "transmission log" records data such as the success or failure of sending notification content, and the time of transmission.

[0445] System Embodiment

[0446] This invention relates to a system that streamlines customer notification operations in corporate sales and automatically generates and sends individually customized notification content. The system consists of the following main components:

[0447] Database for obtaining customer information

[0448] Means for selecting an appropriate template

[0449] Artificial intelligence model for generating customized notification content

[0450] Means for sending notification content to customers

[0451] Program processing

[0452] Data acquisition

[0453] When a user needs to update information related to a specific customer, they send a request to the server via their terminal. The server retrieves the relevant customer information from the database. For example, to retrieve information for customer ID "12345", the server executes an SQL query to obtain the customer's delivery status, schedule, and connection status.

[0454] Template Selection

[0455] The server analyzes the acquired data and selects the template best suited to the customer's situation. For example, if delivery is delayed, a delay notification template will be selected. Different templates are selected depending on whether the delivery is on schedule or for other reasons.

[0456] Custom email generation

[0457] The server uses an artificial intelligence model (e.g., OpenAI's GPT-3) based on the selected template and acquired data to generate customized notification content. Specifically, it replaces placeholders in the template with dynamic data to generate individually customized email bodies.

[0458] Examples of prompt statements are as follows:

[0459] "Please use the following template to generate a customized email regarding a delivery delay for customer ID "12345". Template: Dear {{customer_name}}, We hope this email finds you well. The delivery of product ID: {{product_id}} is delayed. We will contact you later with the new delivery date. Customer data: { "customer_name": "Taro Yamada", "product_id": "XYZ123"}"

[0460] Send email

[0461] After reviewing the generated email content, the server sends the email to the customer's email address via an SMTP server (e.g., Postfix). During sending, a transmission log is recorded, and information such as success or failure of transmission and the time of transmission is stored.

[0462] Specific example

[0463] Let's take the example of a case where the delivery for customer ID "12345" is delayed. In this case, the process proceeds as follows:

[0464] 1. The user enters customer ID "12345" on their terminal and sends a data retrieval request to the server.

[0465] 2. The server retrieves the delivery status, schedule, and connection status of the relevant customer from the database.

[0466] 3. The server analyzes the acquired data and, because a delivery delay has occurred, selects a delay notification template.

[0467] 4. The server generates customized notification content using an AI model based on templates and data.

[0468] Example: "We sincerely apologize, but the delivery of product ID: 12345 is delayed. We will contact you later with the new delivery date."

[0469] 5. The server sends the generated email to the customer's email address.

[0470] In this way, this system streamlines customer notification operations for corporate sales departments and enables the rapid delivery of customized notifications to individual customers.

[0471] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0472] Step 1:

[0473] The user enters a customer information update request on their terminal. This includes entering the customer ID (e.g., 12345) and other necessary information into the input form. When the user clicks the "Submit" button, the information is sent to the server as an HTTP request.

[0474] Input: Customer ID, Request Details

[0475] Output: Sending requested data

[0476] Step 2:

[0477] The server parses the received request data. The server extracts the customer ID from the request data, generates an SQL query to retrieve the corresponding customer information from the database (e.g., MySQL), and executes it. A specific query might be something like "SELECT FROM customers WHERE customer_id = '12345'" and retrieves the results.

[0478] Input: Request data (Customer ID)

[0479] Output: Retrieval of customer information data

[0480] Step 3:

[0481] The server analyzes the acquired customer information data. This analysis is performed using, for example, the Pandas library. The server analyzes information such as the customer's delivery status, schedule, and connection status to determine which template is appropriate. Based on this information, it selects the appropriate template (for example, a delay notification template).

[0482] Input: Customer information data

[0483] Output: Selected template

[0484] Step 4:

[0485] The server uses the selected template and analyzed customer information to send a prompt to a generating AI model (e.g., OpenAI's GPT-3) to generate customized notification content. A prompt might include, "Please use the following template to generate a customized email for when the delivery of customer ID "12345" is delayed." The AI ​​model then generates specific notification content (e.g., "Mr. / Ms. Yamada, we sincerely apologize, but the delivery of product ID: 12345 is delayed.").

[0486] Input: Selected template, customer information

[0487] Output: Customized notification content

[0488] Step 5:

[0489] The server sends the generated notification content to the customer's email address via an SMTP server (e.g., Postfix). The server establishes an SMTP connection and sends the notification content to the customer's email address according to the email sending protocol. After sending is complete, the server records information such as success / failure and sending time in the sending log.

[0490] Input: Customized notification content, customer's email address

[0491] Output: Transmission results, transmission log recording

[0492] By following these steps, this system can quickly and accurately generate and send customized customer notification content.

[0493] (Application Example 1)

[0494] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0495] In today's food delivery industry, the various notification tasks for customers are extremely diverse and difficult to perform efficiently. While it is necessary to quickly notify each customer of their delivery status, estimated arrival time, and delivery person information, customizing the content of these notifications individually is time-consuming. Furthermore, delays in selecting appropriate templates for situations such as delivery delays or special offers can lead to decreased customer satisfaction and reduced operational efficiency.

[0496] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0497] In this invention, the server includes means for selecting a template for notifying customers of various information based on customer information obtained from a database, means for generating customized notification content based on the template, communication means for sending the generated notification content to the customer, and means for sending the notification content in push notification format on various devices. This makes it possible to quickly generate and send individually customized notification content.

[0498] A "database" is an electronic system for systematically organizing information and efficiently searching, updating, and managing it.

[0499] "Customer information" refers to data about the customer, including name, contact information, delivery status, estimated arrival time, and delivery person information.

[0500] A "template" is a document model with a specific format and structure, and serves as a basic framework for automatically generating notification content.

[0501] "Customized notification content" refers to notification messages that are individually tailored based on the specific circumstances and information of a particular customer.

[0502] "Means of generation" refers to devices or programs that have the ability or function to perform a specific process and produce a desired output result.

[0503] "Communication methods" refer to means of sending information to specific recipients, and include email and push notifications.

[0504] "Push notifications" are a notification format that sends information to the user in real time and displays it immediately on the device screen.

[0505] "Delivery status" refers to status information that indicates the stage of delivery for an ordered item in a food delivery service.

[0506] "Estimated arrival time" refers to information indicating the time when a particular delivery is expected to arrive at the designated recipient's location.

[0507] "Delivery driver information" refers to information about the employee responsible for delivery, including their name, contact information, and delivery history.

[0508] A "generative AI model" is an algorithm or data model that uses artificial intelligence to process data and generate output tailored to a specific task or purpose.

[0509] The system for realizing this invention automatically generates and sends individually customized notification content based on customer information obtained from a database. This system consists of the following main components.

[0510] System components

[0511] 1. Database

[0512] A database is an electronic system for systematically organizing customer information and efficiently searching, updating, and managing it. Specifically, it stores customer delivery status, estimated arrival time, and delivery person information.

[0513] 2. Server

[0514] The server retrieves customer information from the database, analyzes that information, and selects the optimal template. Furthermore, it uses a generative AI model to generate customized notification content based on the selected template.

[0515] 3. Means of communication

[0516] The server has communication means to send the generated notification content to various devices. This includes email and push notifications.

[0517] 4. Terminal

[0518] The terminals are devices used by customers and delivery personnel, and include smartphones and tablets. These terminals display information sent as push notifications in real time.

[0519] Program processing

[0520] The server runs using Python and programs such as Flask. It uses sqlite3 for database connections and smtplib for sending emails. OpenAI GPT-3 is used for the generative AI model.

[0521] First, the user sends a request from their device to the server to review or update information related to a specific customer. The server retrieves the customer information from the database, analyzes it, and selects an appropriate notification template. Next, it uses a generative AI model to generate customized notification content based on the template. This notification content includes information such as the customer name, order ID, scheduled arrival time, and new estimated arrival time.

[0522] The generated notification content is sent to various devices via communication means. For example, if it is sent as a push notification to a smartphone, the customer can immediately check the delivery status. The sent notification log is recorded, and information such as the success or failure of the transmission and the time of transmission is stored.

[0523] Specific example

[0524] Here are some specific examples of how customers use food delivery services.

[0525] 1. The user sends a request from their device to the server to check the delivery status.

[0526] 2. The server retrieves the relevant customer information from the database and recognizes that a delivery delay has occurred.

[0527] 3. The server selects a delayed notification template and uses a generation AI model to generate customized notification content.

[0528] 4. The generated notification reads: "We sincerely apologize, but the delivery of your ordered item ID: ABC123 is delayed. The new estimated arrival time is 14:30."

[0529] 5. This notification content will be sent to the smartphone as a push notification via a communication method.

[0530] Example of a prompt

[0531] "Use the generation AI model to generate a delivery delay notification for customer 'Yamada Taro' with order ID 'XYZ789'. The estimated arrival time is '15:00'."

[0532] In this way, the present invention is a system that can streamline customer notification operations in the food delivery industry and improve customer satisfaction.

[0533] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0534] Step 1:

[0535] The user uses a terminal to check or update the delivery status and sends a request to the server. The input is the customer ID and the type of information to be checked, and the output is the request data sent to the server. Once the request is sent, the server receives the data and proceeds to the next step.

[0536] Step 2:

[0537] The server queries the database based on the received request. The input is the customer ID and related request information, and the output is data retrieved from the database, such as the customer's delivery status, estimated arrival time, and delivery person information. The server retrieves the relevant data from the database and prepares it for analysis.

[0538] Step 3:

[0539] The server analyzes the retrieved customer information and selects a template appropriate to the customer's situation. The input is customer information retrieved from the database, and the output is the selected template. For example, if a delivery is delayed, a delay notification template will be selected.

[0540] Step 4:

[0541] The server generates customized notification content using a generative AI model based on the selected template and retrieved data. The input is the template and customer information, and the output is a specific notification message. Specifically, the AI ​​model inserts the customer's specific data into placeholders within the template to generate the final notification content.

[0542] Step 5:

[0543] The server reviews the generated notification content and sends it to the customer via a communication method. The input is the generated notification message, and the output is the notification sent to various devices. Specifically, the server either sends an email using an SMTP server or sends a real-time notification to a smartphone using a push notification system.

[0544] Step 6:

[0545] The server logs sent notifications, saving information such as success, failure, and transmission time. Input is the status information of the transmission result, and output is the transmission history stored in log files or a database. This enables troubleshooting and history auditing.

[0546] This entire processing step allows users to track the delivery status in real time and receive personalized notifications quickly.

[0547] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0548] System Embodiment

[0549] This invention relates to a system that streamlines customer communication in corporate sales, automatically generates customized notification content, and further customizes it based on user sentiment. The main components of the system include the following:

[0550] database

[0551] Template selection method

[0552] Artificial intelligence that generates customized notification content

[0553] Means of sending notification content to customers

[0554] Emotional Engine

[0555] Program processing

[0556] 1. User requests and data acquisition

[0557] A user requests updates regarding specific customer information via their device. The user enters the customer ID and sends a data retrieval request to the server. The server retrieves the customer information from the database. This information includes delivery status, schedule, and activation status.

[0558] 2. Emotion recognition

[0559] The device sends the user's facial expressions, voice, or text input to the emotion engine. The emotion engine analyzes this data to recognize the user's emotions. For example, if it determines that the user is feeling anxious, it customizes the notification content based on that information.

[0560] 3. Template Selection

[0561] The server analyzes the acquired customer information and sentiment data obtained from the sentiment engine, and selects an appropriate template based on this analysis. For example, if the sentiment engine determines that the user is anxious, it will select a template that provides a greater sense of reassurance.

[0562] 4. Generating customized emails

[0563] The server uses the AI ​​Writer extension to generate customized notification content based on the selected template, acquired data, and sentiment data. Specifically, it replaces placeholders within the template with dynamic data and sentiment-based content.

[0564] 5. Send email

[0565] The server sends the generated customized notification content to the customer using an SMTP server. After the transmission is complete, a transmission log is recorded for later review.

[0566] Specific example

[0567] Let's take the example of how to handle a situation where a delivery to customer "12345" is delayed, and the user is feeling anxious about this situation.

[0568] 1. The terminal enters customer ID "12345" and sends a data retrieval request to the server.

[0569] 2. The server retrieves customer delivery status, schedule, and activation status from the database.

[0570] 3. Simultaneously, the device transmits the user's facial expressions and voice to the emotion engine, which recognizes that the user is feeling anxious.

[0571] 4. The server analyzes the acquired data and sentiment data, selects a "delayed notification template," and then adds "content that provides a sense of relief."

[0572] 5. The server uses an AI Writer to generate customized notification content.

[0573] Example: "Customer, there is a delay in the delivery of product ID: 12345. We will contact you shortly with the new delivery date. We apologize for any inconvenience this may cause. Please contact us if you have any questions or concerns."

[0574] 6. The server sends the generated email to the customer "customer@example.com" and records the sending log.

[0575] These processes enable efficient customer notifications and allow for customization based on user emotions, which is expected to improve operational efficiency and customer satisfaction.

[0576] The following describes the processing flow.

[0577] Step 1:

[0578] The user requests an update to customer information via their device. Specifically, the user enters a specific customer ID in the GUI and clicks the "Get Data" button.

[0579] Step 2:

[0580] The device sends the user's request to the server as an API request. The request includes the specified customer ID.

[0581] Step 3:

[0582] The server receives the API request and sends a query to the database based on the specified customer ID. For example, it retrieves the delivery status, schedule, and activation status for customer ID "12345".

[0583] Step 4:

[0584] The server analyzes customer information retrieved from the database. For example, it checks whether deliveries are delayed or whether the schedule is on track.

[0585] Step 5:

[0586] The device collects data to recognize the user's emotions. Specifically, it captures facial expressions with the device's camera, collects voice tone with the microphone, and analyzes text input.

[0587] Step 6:

[0588] The device sends collected emotional data to the emotion engine. The emotion engine analyzes this data and recognizes the user's emotions. For example, it might determine that the user is feeling anxious.

[0589] Step 7:

[0590] The server selects a template based on customer information and sentiment data it has acquired. If delivery is delayed, it selects a delay notification template, and if the user is feeling anxious, it selects a template that includes content to provide reassurance.

[0591] Step 8:

[0592] The server loads a selected template and uses the AI ​​Writer extension to customize the notification content. For example, it generates emails that include messages such as "Delivery is delayed," "New deadline announcement," and "Message to alleviate concerns."

[0593] Step 9:

[0594] The server verifies the generated customized email content and sends it to the customer's email address via the SMTP server. For example, it sends an email to "customer@example.com".

[0595] Step 10:

[0596] The server records transmission logs. It saves information such as whether the transmission was successful or unsuccessful, and the transmission time, so that it can be reviewed later.

[0597] Step 11:

[0598] Users can check the sending logs as needed to evaluate whether notifications were delivered successfully. The logs contain detailed records of the sending status of each email.

[0599] In this way, the system efficiently performs a series of processes, from acquiring customer information to generating customized notification content, analyzing sentiment data, and sending emails, enabling it to respond in a way that takes user emotions into consideration.

[0600] (Example 2)

[0601] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0602] In modern corporate sales, it is crucial to streamline communication with customers while generating customized notifications tailored to individual customer needs. However, while traditional systems could generate automated notifications based on customer information, they did not further customize the notification content to consider user emotions. As a result, customers received standardized messages, and it was difficult to respond in a way that took individual circumstances and emotions into account. Furthermore, the manual process of selecting templates and customizing notification content was also inefficient.

[0603] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for selecting a template for notifying customers of various information based on customer information obtained from a database, means for analyzing the obtained customer information and user sentiment data to select the optimal template, means for using artificial intelligence to generate customized notification content based on the selected template, and means for sending the generated notification content to the customer. This makes it possible to generate more personalized notification content based on the user's sentiment, thereby improving customer satisfaction. Furthermore, automated template selection and notification content generation can improve operational efficiency.

[0604] A "database" is a computer system that systematically stores information and data, making it searchable and retrievable.

[0605] "Customer information" refers to data about a customer, including information such as delivery status, schedule, and activation status.

[0606] A "template" is a pre-configured document or format tailored to a specific purpose, and it forms the basis of the notification content.

[0607] "User emotion data" refers to data related to emotions analyzed from the user's facial expressions, voice, or text input.

[0608] "Analysis" is the process of examining data and information in detail to find patterns, trends, and relationships within them.

[0609] "Artificial intelligence" is a technology that enables machines to learn, make decisions, and solve problems like humans, and in this invention, it is used to generate customized notification content.

[0610] "Notification content" refers to the information and messages that should be conveyed to the customer, and is customized based on templates and sentiment data.

[0611] "Transmission" refers to the act of delivering information or data to another system or user through a computer system.

[0612] The system of this invention is designed to streamline communication with customers in corporate sales and to automatically generate and send customized notification content based on the user's emotions to the customer. The main components of the system include a database, a template selection means, artificial intelligence for generating customized notification content, means for sending the notification content to the customer, and an emotion engine.

[0613] Specific processing of the program

[0614] The system processes are structured as follows:

[0615] 1. User requests and data acquisition

[0616] A user requests updates regarding specific customer information via their device. The user enters the customer ID into the device and sends a data retrieval request to the server. The server retrieves the relevant customer information (delivery status, schedule, activation status, etc.) from the database.

[0617] 2. Emotion recognition

[0618] The device transmits the user's facial expressions, voice, and text input to the emotion engine in real time. The emotion engine analyzes this data and recognizes the emotions the user is feeling (e.g., anxiety, joy). This emotion data is sent to a server and stored there.

[0619] 3. Template Selection

[0620] The server analyzes the acquired customer information and sentiment data to select a notification template. The server uses rule-based algorithms or machine learning models to choose the best one from several pre-configured email templates.

[0621] 4. Generating customized emails

[0622] The server uses its AI Writer function to generate customized notification content based on the selected template, acquired data, and sentiment data. Specifically, it replaces placeholders within the template with dynamic data and sentiment-based content.

[0623] 5. Send email

[0624] The server uses an SMTP server to send the generated customized notification content to the specified customer email address. After sending, the server records the sending result and saves it to a log file or database for later review.

[0625] Hardware and software to be used

[0626] Database: A database system for storing and managing customer information (delivery status, schedule, activation status, etc.).

[0627] Template selection method: Program logic or algorithm executed within the server.

[0628] Artificial intelligence: AI modules for generating customized notification content (e.g., AI Writer).

[0629] Emotion Engine: A software module equipped with facial recognition and speech analysis capabilities.

[0630] SMTP server: A mail sending server used to send notification content to customers.

[0631] Specific example

[0632] The following describes how to handle a situation where a delivery to customer "12345" is delayed and the user is feeling anxious about the situation.

[0633] 1. User requests and data acquisition

[0634] The user enters customer ID "12345" into the terminal and sends a data retrieval request to the server.

[0635] The server retrieves customer delivery status, schedule, and activation status from the database.

[0636] 2. Emotion recognition

[0637] The device transmits the user's facial expressions and voice to the emotion engine, which recognizes that the user is feeling anxious.

[0638] 3. Template Selection

[0639] The server analyzes the acquired data and sentiment data, selects a "delayed notification template," and then adds "content that provides a sense of relief."

[0640] 4. Generating customized emails

[0641] The server uses an AI Writer to generate customized notification content.

[0642] Example: "Customer, there is a delay in the delivery of product ID: 12345. We will contact you shortly with the new delivery date. We apologize for any inconvenience this may cause. Please contact us if you have any questions or concerns."

[0643] 5. Send email

[0644] The server sends the generated email to the customer "customer@example.com" and records the sending log.

[0645] Example of a prompt

[0646] Prompt: "Generate a customized email to reassure a customer whose delivery is delayed. The customer ID is 12345."

[0647] Expected output example:

[0648] "Dear customer, there is a delay in the delivery of product ID: 12345. We will contact you shortly with the new delivery date. We apologize for any inconvenience this may cause. Please contact us if you have any questions or concerns."

[0649] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0650] Processing flow

[0651] Step 1:

[0652] A user requests updates regarding specific customer information via their device. Specifically, the user logs into the device, enters the customer ID, and clicks the "Get Data" button. This action causes the device to send a data retrieval request, including the customer ID, to the server. The input is the customer ID, and the output is a request message containing the data retrieval request. The server receives the request and creates and executes a database query.

[0653] Step 2:

[0654] The server queries the database to retrieve customer information. This process uses the customer ID submitted as input to retrieve information such as the customer's delivery status, schedule, and activation status from the database. Specifically, an SQL query like "SELECT FROM customer_information WHERE customer_ID = '12345'" is executed. The output is a customer_information dataset as the query result.

[0655] Step 3:

[0656] The device captures the user's facial expressions, voice, and text input in real time. The device sends the captured data to an emotion engine, which analyzes it to generate the user's emotion data. The input consists of the user's facial image and voice data, which are processed by facial recognition algorithms and voice analysis algorithms. The output is the analyzed emotion data (e.g., anxiety, joy).

[0657] Step 4:

[0658] The server selects the most suitable template based on the acquired customer information and sentiment data. The server uses a rule-based algorithm or machine learning model to select the appropriate template from its template storage. The input is the acquired customer information and sentiment data, and the output is the selected notification template. For example, if a customer's delivery is delayed and the user is feeling anxious, the "delay notification template" will be selected.

[0659] Step 5:

[0660] The server generates customized notification content based on the selected template, acquired data, and sentiment data. Specifically, the AI ​​Writer function replaces placeholders in the template with dynamic data and sentiment-based content. The input is the selected template, customer information, and sentiment data, and the output is the generated customized notification content. For example, an email message like, "Dear customer, there is a delay in the delivery of product ID: 12345. We will contact you shortly with the new delivery date. We apologize for any inconvenience this may cause. Please contact us if you have any questions or concerns," is generated.

[0661] Step 6:

[0662] The server sends the generated customized notification content to the specified customer email address using an SMTP server. The inputs are the generated notification content and the customer's email address, and the output is the sent email and its result. This process includes connecting to the SMTP server, establishing an email sending session, sending the email content, and recording the sending log. After sending is complete, the sending log is recorded on the server for later review.

[0663] This allows the system to efficiently notify customers and provide customized notification content that takes user emotions into consideration.

[0664] (Application Example 2)

[0665] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0666] Conventional customer information notification systems have difficulty accurately reflecting customers' real-time emotions and intentions in their communication, resulting in problems such as decreased customer satisfaction and reduced sales efficiency. Furthermore, notification content based on standard templates lacks individualized attention to customers, potentially leading to missed business opportunities.

[0667] In Application Example 2, the specific processing performed by the specific processing unit 290 of the data processing device 12 is realized by the following means. In this invention, the server includes means for selecting a template for notifying customers of various information based on customer information obtained from a database, means for generating customized notification content based on the template, means for sending the generated notification content to the customer, and means for analyzing the user's emotions using an emotion recognition device and further customizing the notification content based on the results. This enables highly accurate customer service in real time, improving customer satisfaction and sales efficiency.

[0668] A "database" is an information management system that stores customer information and allows it to be searched and retrieved as needed.

[0669] A "template selection mechanism" is a means that has the function of automatically selecting an appropriate notification template based on customer information.

[0670] "Means for generating customized notification content" refers to methods for creating individually tailored notification content based on selected templates and customer data.

[0671] "Means for sending notification content to customers" refers to means that have the function of sending the generated notification content to customers.

[0672] An "emotion recognition device" is a device or software that analyzes a user's emotions from their facial expressions, voice, etc., and recognizes a specific emotional state.

[0673] "Visit history" refers to information about a customer's history of visiting a store, including the date, time, and frequency of visits.

[0674] "Purchase history" refers to a record of information about products and services that a customer has purchased in the past.

[0675] "Facial expression" refers to the emotional state indicated by the movement of a customer's facial muscles.

[0676] "Voice" refers to an audio signal used to recognize an emotional state by analyzing the customer's voice characteristics, such as tone, pitch, and speed.

[0677] "Artificial intelligence" refers to computer algorithms or software that learn from large amounts of data and automatically perform specific tasks.

[0678] A "generative AI model" is a model that uses artificial intelligence technology to automatically generate content from input data.

[0679] "Real-time" refers to a state where processing and responses occur almost immediately after an event takes place, with virtually no delay.

[0680] A description of an embodiment for carrying out this invention will be provided. This system performs customer information acquisition, sentiment recognition, template selection, customized notification generation, and notification transmission in a series of steps.

[0681] Hardware and software to be used

[0682] hardware

[0683] Smartphones: Used by store staff, they function as input devices for acquiring customer information and recognizing emotions.

[0684] Server: The central hardware that performs data processing and runs AI models.

[0685] software

[0686] Database: Stores and manages customer information (visit history, purchase history, etc.).

[0687] EmotionEngine: Software that analyzes and recognizes emotions from the user's facial expressions and voice.

[0688] TemplateSelector: Software that selects the appropriate template based on customer information and sentiment data.

[0689] AIWriter: An artificial intelligence model that generates customized notification content based on analysis results.

[0690] SMTP server: A mail server used to send generated notification content to customers.

[0691] Data processing and data calculation workflow

[0692] 1. Data Acquisition

[0693] The server retrieves customer information (visit history, purchase history, etc.) from the database. The user (employee) enters the customer ID into their smartphone and sends a data retrieval request to the server. The server accesses the database and retrieves the necessary information.

[0694] 2. Emotion recognition

[0695] Users interact with customers via their smartphones and capture their facial expressions with the camera. The smartphones send this data to an emotion recognition device called EmotionEngine, which analyzes and recognizes emotional data. For example, it can identify emotions such as "dissatisfaction" or "reassurance" from facial expressions and tone of voice.

[0696] 3. Template Selection

[0697] The server uses TemplateSelector to choose an appropriate template based on the acquired customer information and analyzed sentiment data. This template is the basic text for efficiently structuring notification content.

[0698] 4. Generate customized notifications

[0699] The server uses AIWriter to customize the selected template based on customer information and sentiment data. The generated notification content is tailored to each customer.

[0700] 5. Send Notification

[0701] The server sends the generated customized notification content to the customer using an SMTP server. After sending, a transmission log is recorded for later review.

[0702] Specific example

[0703] scenario

[0704] Customer "Customer ID: 54321" enters the store. A store employee uses a smartphone app to retrieve customer information. Based on the customer's facial expression, it is determined that the customer is dissatisfied with the waiting time.

[0705] Prompts for Generative AI Models

[0706] Please retrieve the information for customer ID: 54321.

[0707] We recognized that the customer was dissatisfied.

[0708] Choose an appropriate template and create a customized notification that includes reassuring content.

[0709] This will allow for more efficient and effective customer service in physical stores, leading to improved customer satisfaction and increased operational efficiency.

[0710] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0711] Step 1:

[0712] The user enters their customer ID using their smartphone and sends a data retrieval request to the server. The server retrieves customer information corresponding to the entered customer ID from the database and responds. The input is the customer ID, and the output is the corresponding customer information (visit history, purchase history, etc.).

[0713] Step 2:

[0714] The terminal interacts with the customer and captures their facial expressions using its camera, sending the collected data to the EmotionEngine, an emotion recognition device. The EmotionEngine analyzes this data and outputs the customer's emotional data (e.g., dissatisfaction, relief, etc.). The input is emotional input data such as facial expressions and voice, and the output is the recognized emotional data.

[0715] Step 3:

[0716] The server uses TemplateSelector to choose the optimal template based on the acquired customer information and emotion data from EmotionEngine. In this process, the server determines the template considering the customer's state and emotions. The input is customer information and emotion data, and the output is the selected template.

[0717] Step 4:

[0718] The server sends the selected template, retrieved customer information, and sentiment data to the AIWriter to generate customized notification content. The AIWriter uses this information to replace the template's placeholders with dynamic data and sentiment-based content. The inputs are the template, customer information, and sentiment data, while the output is the customized notification content.

[0719] Step 5:

[0720] The server sends the generated customized notification content to the customer using an SMTP server. After the email is delivered to the customer via the SMTP server, a transmission log is recorded for later review. The input is the customized notification content, and the output is the transmission log and delivery to the customer.

[0721] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0722] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0723] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0724] [Third Embodiment]

[0725] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0726] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0727] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0728] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0729] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0730] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0731] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0732] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0733] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0734] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0735] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0736] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0737] System Embodiment

[0738] This invention relates to a system that streamlines customer notification operations in corporate sales and automatically generates and sends individually customized notification content. The system consists of the following main components:

[0739] Database for obtaining customer information

[0740] Means for selecting an appropriate template

[0741] Artificial intelligence for generating customized notification content

[0742] Means for sending notification content to customers

[0743] Program processing

[0744] 1. Data Acquisition

[0745] When a user needs to update information related to a specific customer, they send a request to the server via their terminal. The server retrieves the relevant customer information from the database, namely delivery status, schedule, and activation status. For example, to retrieve information for customer ID "12345", the server retrieves the relevant data from the database via a query.

[0746] 2. Template Selection

[0747] The server analyzes the acquired data and selects the template best suited to the customer's situation. For example, if delivery is delayed, a delay notification template is selected. Different templates are chosen depending on whether the delivery is on schedule or for other reasons.

[0748] 3. Generate customized emails

[0749] The server uses the AI ​​Writer extension to generate customized notification content based on the selected template and retrieved data. Specifically, it replaces placeholders in the template with dynamic data to generate individually customized email bodies.

[0750] 4. Send email

[0751] After reviewing the generated email content, the server sends the email to the customer's email address via the SMTP server. During sending, a transmission log is recorded, and information such as the success or failure of the transmission and the time of transmission is stored.

[0752] Specific example

[0753] Let's take the example of a case where delivery to customer "12345" is delayed. In this case, the process proceeds as follows:

[0754] 1. The terminal enters customer ID "12345" and sends a data retrieval request to the server.

[0755] 2. The server retrieves the delivery status, schedule, and activation status of the relevant customer from the database.

[0756] 3. The server analyzes the acquired data and, because a delivery delay has occurred, selects a delay notification template.

[0757] 4. The server generates customized notification content using AI Writer based on templates and data.

[0758] Example: "We sincerely apologize, but the delivery of product ID: 12345 is delayed. We will contact you later with the new delivery date."

[0759] 5. The server sends the generated email to "customer@example.com".

[0760] In this way, this system streamlines customer notification operations for corporate sales departments and enables the rapid delivery of customized notifications to individual customers.

[0761] The following describes the processing flow.

[0762] Step 1:

[0763] A user requests to view or send updated information about a specific customer via their device. The user uses a GUI to enter the relevant customer ID and triggers a data retrieval request.

[0764] Step 2:

[0765] The device sends the user's request to the server as an API request. The request includes the customer ID and the necessary information.

[0766] Step 3:

[0767] The server receives the request and sends a query to the database based on the specified customer ID. The server retrieves customer information, including delivery status, schedule, and activation status.

[0768] Step 4:

[0769] The server analyzes customer information retrieved from the database and selects a template appropriate to the situation. For example, if delivery is delayed, a delay notification template will be selected.

[0770] Step 5:

[0771] The server loads a selected template and generates customized notification content using an AI Writer extension based on customer information. The template's placeholders are replaced with dynamic data, creating individually customized email content.

[0772] Step 6:

[0773] The server passes the generated notification content to the SMTP server, which then sends an email to the customer's email address. The outgoing email contains dynamically generated customized content.

[0774] Step 7:

[0775] The server records email sending logs. It saves information such as whether the email was sent successfully or not, and the time of sending, to facilitate later review and troubleshooting.

[0776] Step 8:

[0777] Users can check the sending logs as needed to evaluate whether notifications were delivered successfully. The logs contain detailed records of the sending status of each email.

[0778] These steps enable the system to perform customer notification tasks efficiently and effectively, and to quickly deliver customized notifications to individual customers.

[0779] (Example 1)

[0780] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0781] In corporate sales, customer notification tasks require the rapid generation and efficient transmission of individually customized notification content. Traditional manual notification methods are time-consuming, labor-intensive, and prone to human error. Furthermore, selecting and customizing templates to suit diverse customer situations is difficult, making them unsuitable for today's business environment where quick and accurate responses are essential.

[0782] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0783] In this invention, the server includes means for obtaining specific customer information based on a request received from a device, means for obtaining customer information from a database using queries, means for analyzing the obtained customer information and selecting an appropriate template, means for generating customized notification content using an artificial intelligence model based on the selected template and obtained data, means for sending the generated notification content to the customer, and means for recording a transmission log. This makes it possible to automate customer notification operations and provide customized notification content quickly and accurately.

[0784] A "device" is an input device that sends a request to retrieve customer information to a server, or a device that has that function.

[0785] A "request" is data that a device sends to a server to request specific customer information.

[0786] A "server" is a central processing unit that acquires, analyzes, generates, and transmits customer information.

[0787] A "database" is a data storage system that manages and stores customer information.

[0788] A "query" is a command or question that is executed against a database to retrieve specific information.

[0789] "Customer information" refers to data related to a customer, including information such as shipping status, schedule, and connection status.

[0790] A "template" is a format for describing notification content, and it includes placeholders that are appropriate for specific situations.

[0791] An "artificial intelligence model" is an algorithm or program that uses machine learning or deep learning techniques to generate customized notification content.

[0792] "Notification content" refers to the message sent to the customer, generated based on a template and customer information.

[0793] "Transmission means" refers to the means of communication used to send the generated notification content to the customer.

[0794] A "transmission log" records data such as the success or failure of sending notification content, and the time of transmission.

[0795] System Embodiment

[0796] This invention relates to a system that streamlines customer notification operations in corporate sales and automatically generates and sends individually customized notification content. The system consists of the following main components:

[0797] Database for obtaining customer information

[0798] Means for selecting an appropriate template

[0799] Artificial intelligence model for generating customized notification content

[0800] Means for sending notification content to customers

[0801] Program processing

[0802] Data acquisition

[0803] When a user needs to update information related to a specific customer, they send a request to the server via their terminal. The server retrieves the relevant customer information from the database. For example, to retrieve information for customer ID "12345", the server executes an SQL query to obtain the customer's delivery status, schedule, and connection status.

[0804] Template Selection

[0805] The server analyzes the acquired data and selects the template best suited to the customer's situation. For example, if delivery is delayed, a delay notification template will be selected. Different templates are selected depending on whether the delivery is on schedule or for other reasons.

[0806] Custom email generation

[0807] The server uses an artificial intelligence model (e.g., OpenAI's GPT-3) based on the selected template and acquired data to generate customized notification content. Specifically, it replaces placeholders in the template with dynamic data to generate individually customized email bodies.

[0808] Examples of prompt statements are as follows:

[0809] "Please use the following template to generate a customized email regarding a delivery delay for customer ID "12345". Template: Dear {{customer_name}}, We hope this email finds you well. The delivery of product ID: {{product_id}} is delayed. We will contact you later with the new delivery date. Customer data: { "customer_name": "Taro Yamada", "product_id": "XYZ123"}"

[0810] Send email

[0811] After reviewing the generated email content, the server sends the email to the customer's email address via an SMTP server (e.g., Postfix). During sending, a transmission log is recorded, and information such as success or failure of transmission and the time of transmission is stored.

[0812] Specific example

[0813] Let's take the example of a case where the delivery for customer ID "12345" is delayed. In this case, the process proceeds as follows:

[0814] 1. The user enters customer ID "12345" on their terminal and sends a data retrieval request to the server.

[0815] 2. The server retrieves the delivery status, schedule, and connection status of the relevant customer from the database.

[0816] 3. The server analyzes the acquired data and, because a delivery delay has occurred, selects a delay notification template.

[0817] 4. The server generates customized notification content using an AI model based on templates and data.

[0818] Example: "We sincerely apologize, but the delivery of product ID: 12345 is delayed. We will contact you later with the new delivery date."

[0819] 5. The server sends the generated email to the customer's email address.

[0820] In this way, this system streamlines customer notification operations for corporate sales departments and enables the rapid delivery of customized notifications to individual customers.

[0821] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0822] Step 1:

[0823] The user enters a customer information update request on their terminal. This includes entering the customer ID (e.g., 12345) and other necessary information into the input form. When the user clicks the "Submit" button, the information is sent to the server as an HTTP request.

[0824] Input: Customer ID, Request Details

[0825] Output: Sending requested data

[0826] Step 2:

[0827] The server parses the received request data. The server extracts the customer ID from the request data, generates an SQL query to retrieve the corresponding customer information from the database (e.g., MySQL), and executes it. A specific query might be something like "SELECT FROM customers WHERE customer_id = '12345'" and retrieves the results.

[0828] Input: Request data (Customer ID)

[0829] Output: Retrieval of customer information data

[0830] Step 3:

[0831] The server analyzes the acquired customer information data. This analysis is performed using, for example, the Pandas library. The server analyzes information such as the customer's delivery status, schedule, and connection status to determine which template is appropriate. Based on this information, it selects the appropriate template (for example, a delay notification template).

[0832] Input: Customer information data

[0833] Output: Selected template

[0834] Step 4:

[0835] The server uses the selected template and analyzed customer information to send a prompt to a generating AI model (e.g., OpenAI's GPT-3) to generate customized notification content. A prompt might include, "Please use the following template to generate a customized email for when the delivery of customer ID "12345" is delayed." The AI ​​model then generates specific notification content (e.g., "Mr. / Ms. Yamada, we sincerely apologize, but the delivery of product ID: 12345 is delayed.").

[0836] Input: Selected template, customer information

[0837] Output: Customized notification content

[0838] Step 5:

[0839] The server sends the generated notification content to the customer's email address via an SMTP server (e.g., Postfix). The server establishes an SMTP connection and sends the notification content to the customer's email address according to the email sending protocol. After sending is complete, the server records information such as success / failure and sending time in the sending log.

[0840] Input: Customized notification content, customer's email address

[0841] Output: Transmission results, transmission log recording

[0842] By following these steps, this system can quickly and accurately generate and send customized customer notification content.

[0843] (Application Example 1)

[0844] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0845] In today's food delivery industry, the various notification tasks for customers are extremely diverse and difficult to perform efficiently. While it is necessary to quickly notify each customer of their delivery status, estimated arrival time, and delivery person information, customizing the content of these notifications individually is time-consuming. Furthermore, delays in selecting appropriate templates for situations such as delivery delays or special offers can lead to decreased customer satisfaction and reduced operational efficiency.

[0846] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0847] In this invention, the server includes means for selecting a template for notifying customers of various information based on customer information obtained from a database, means for generating customized notification content based on the template, communication means for sending the generated notification content to the customer, and means for sending the notification content in push notification format on various devices. This makes it possible to quickly generate and send individually customized notification content.

[0848] A "database" is an electronic system for systematically organizing information and efficiently searching, updating, and managing it.

[0849] "Customer information" refers to data about the customer, including name, contact information, delivery status, estimated arrival time, and delivery person information.

[0850] A "template" is a document model with a specific format and structure, and serves as a basic framework for automatically generating notification content.

[0851] "Customized notification content" refers to notification messages that are individually tailored based on the specific circumstances and information of a particular customer.

[0852] "Means of generation" refers to devices or programs that have the ability or function to perform a specific process and produce a desired output result.

[0853] "Communication methods" refer to means of sending information to specific recipients, and include email and push notifications.

[0854] "Push notifications" are a notification format that sends information to the user in real time and displays it immediately on the device screen.

[0855] "Delivery status" refers to status information that indicates the stage of delivery for an ordered item in a food delivery service.

[0856] "Estimated arrival time" refers to information indicating the time when a particular delivery is expected to arrive at the designated recipient's location.

[0857] "Delivery driver information" refers to information about the employee responsible for delivery, including their name, contact information, and delivery history.

[0858] A "generative AI model" is an algorithm or data model that uses artificial intelligence to process data and generate output tailored to a specific task or purpose.

[0859] The system for realizing this invention automatically generates and sends individually customized notification content based on customer information obtained from a database. This system consists of the following main components.

[0860] System components

[0861] 1. Database

[0862] A database is an electronic system for systematically organizing customer information and efficiently searching, updating, and managing it. Specifically, it stores customer delivery status, estimated arrival time, and delivery person information.

[0863] 2. Server

[0864] The server retrieves customer information from the database, analyzes that information, and selects the optimal template. Furthermore, it uses a generative AI model to generate customized notification content based on the selected template.

[0865] 3. Means of communication

[0866] The server has communication means to send the generated notification content to various devices. This includes email and push notifications.

[0867] 4. Terminal

[0868] The terminals are devices used by customers and delivery personnel, and include smartphones and tablets. These terminals display information sent as push notifications in real time.

[0869] Program processing

[0870] The server runs using Python and programs such as Flask. It uses sqlite3 for database connections and smtplib for sending emails. OpenAI GPT-3 is used for the generative AI model.

[0871] First, the user sends a request from their device to the server to review or update information related to a specific customer. The server retrieves the customer information from the database, analyzes it, and selects an appropriate notification template. Next, it uses a generative AI model to generate customized notification content based on the template. This notification content includes information such as the customer name, order ID, scheduled arrival time, and new estimated arrival time.

[0872] The generated notification content is sent to various devices via communication means. For example, if it is sent as a push notification to a smartphone, the customer can immediately check the delivery status. The sent notification log is recorded, and information such as the success or failure of the transmission and the time of transmission is stored.

[0873] Specific example

[0874] Here are some specific examples of how customers use food delivery services.

[0875] 1. The user sends a request from their device to the server to check the delivery status.

[0876] 2. The server retrieves the relevant customer information from the database and recognizes that a delivery delay has occurred.

[0877] 3. The server selects a delayed notification template and uses a generation AI model to generate customized notification content.

[0878] 4. The generated notification reads: "We sincerely apologize, but the delivery of your ordered item ID: ABC123 is delayed. The new estimated arrival time is 14:30."

[0879] 5. This notification content will be sent to the smartphone as a push notification via a communication method.

[0880] Example of a prompt

[0881] "Use the generation AI model to generate a delivery delay notification for customer 'Yamada Taro' with order ID 'XYZ789'. The estimated arrival time is '15:00'."

[0882] In this way, the present invention is a system that can streamline customer notification operations in the food delivery industry and improve customer satisfaction.

[0883] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0884] Step 1:

[0885] The user uses a terminal to check or update the delivery status and sends a request to the server. The input is the customer ID and the type of information to be checked, and the output is the request data sent to the server. Once the request is sent, the server receives the data and proceeds to the next step.

[0886] Step 2:

[0887] The server queries the database based on the received request. The input is the customer ID and related request information, and the output is data retrieved from the database, such as the customer's delivery status, estimated arrival time, and delivery person information. The server retrieves the relevant data from the database and prepares it for analysis.

[0888] Step 3:

[0889] The server analyzes the retrieved customer information and selects a template appropriate to the customer's situation. The input is customer information retrieved from the database, and the output is the selected template. For example, if a delivery is delayed, a delay notification template will be selected.

[0890] Step 4:

[0891] The server generates customized notification content using a generative AI model based on the selected template and retrieved data. The input is the template and customer information, and the output is a specific notification message. Specifically, the AI ​​model inserts the customer's specific data into placeholders within the template to generate the final notification content.

[0892] Step 5:

[0893] The server reviews the generated notification content and sends it to the customer via a communication method. The input is the generated notification message, and the output is the notification sent to various devices. Specifically, the server either sends an email using an SMTP server or sends a real-time notification to a smartphone using a push notification system.

[0894] Step 6:

[0895] The server logs sent notifications, saving information such as success, failure, and transmission time. Input is the status information of the transmission result, and output is the transmission history stored in log files or a database. This enables troubleshooting and history auditing.

[0896] This entire processing step allows users to track the delivery status in real time and receive personalized notifications quickly.

[0897] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0898] System Embodiment

[0899] This invention relates to a system that streamlines customer communication in corporate sales, automatically generates customized notification content, and further customizes it based on user sentiment. The main components of the system include the following:

[0900] database

[0901] Template selection method

[0902] Artificial intelligence that generates customized notification content

[0903] Means of sending notification content to customers

[0904] Emotional Engine

[0905] Program processing

[0906] 1. User requests and data acquisition

[0907] A user requests updates regarding specific customer information via their device. The user enters the customer ID and sends a data retrieval request to the server. The server retrieves the customer information from the database. This information includes delivery status, schedule, and activation status.

[0908] 2. Emotion recognition

[0909] The device sends the user's facial expressions, voice, or text input to the emotion engine. The emotion engine analyzes this data to recognize the user's emotions. For example, if it determines that the user is feeling anxious, it customizes the notification content based on that information.

[0910] 3. Template Selection

[0911] The server analyzes the acquired customer information and sentiment data obtained from the sentiment engine, and selects an appropriate template based on this analysis. For example, if the sentiment engine determines that the user is anxious, it will select a template that provides a greater sense of reassurance.

[0912] 4. Generating customized emails

[0913] The server uses the AI ​​Writer extension to generate customized notification content based on the selected template, acquired data, and sentiment data. Specifically, it replaces placeholders within the template with dynamic data and sentiment-based content.

[0914] 5. Send email

[0915] The server sends the generated customized notification content to the customer using an SMTP server. After the transmission is complete, a transmission log is recorded for later review.

[0916] Specific example

[0917] Let's take the example of how to handle a situation where a delivery to customer "12345" is delayed, and the user is feeling anxious about this situation.

[0918] 1. The terminal enters customer ID "12345" and sends a data retrieval request to the server.

[0919] 2. The server retrieves customer delivery status, schedule, and activation status from the database.

[0920] 3. Simultaneously, the device transmits the user's facial expressions and voice to the emotion engine, which recognizes that the user is feeling anxious.

[0921] 4. The server analyzes the acquired data and sentiment data, selects a "delayed notification template," and then adds "content that provides a sense of relief."

[0922] 5. The server uses an AI Writer to generate customized notification content.

[0923] Example: "Customer, there is a delay in the delivery of product ID: 12345. We will contact you shortly with the new delivery date. We apologize for any inconvenience this may cause. Please contact us if you have any questions or concerns."

[0924] 6. The server sends the generated email to the customer "customer@example.com" and records the sending log.

[0925] These processes enable efficient customer notifications and allow for customization based on user emotions, which is expected to improve operational efficiency and customer satisfaction.

[0926] The following describes the processing flow.

[0927] Step 1:

[0928] The user requests an update to customer information via their device. Specifically, the user enters a specific customer ID in the GUI and clicks the "Get Data" button.

[0929] Step 2:

[0930] The device sends the user's request to the server as an API request. The request includes the specified customer ID.

[0931] Step 3:

[0932] The server receives the API request and sends a query to the database based on the specified customer ID. For example, it retrieves the delivery status, schedule, and activation status for customer ID "12345".

[0933] Step 4:

[0934] The server analyzes customer information retrieved from the database. For example, it checks whether deliveries are delayed or whether the schedule is on track.

[0935] Step 5:

[0936] The device collects data to recognize the user's emotions. Specifically, it captures facial expressions with the device's camera, collects voice tone with the microphone, and analyzes text input.

[0937] Step 6:

[0938] The device sends collected emotional data to the emotion engine. The emotion engine analyzes this data and recognizes the user's emotions. For example, it might determine that the user is feeling anxious.

[0939] Step 7:

[0940] The server selects a template based on customer information and sentiment data it has acquired. If delivery is delayed, it selects a delay notification template, and if the user is feeling anxious, it selects a template that includes content to provide reassurance.

[0941] Step 8:

[0942] The server loads a selected template and uses the AI ​​Writer extension to customize the notification content. For example, it generates emails that include messages such as "Delivery is delayed," "New deadline announcement," and "Message to alleviate concerns."

[0943] Step 9:

[0944] The server verifies the generated customized email content and sends it to the customer's email address via the SMTP server. For example, it sends an email to "customer@example.com".

[0945] Step 10:

[0946] The server records transmission logs. It saves information such as whether the transmission was successful or unsuccessful, and the transmission time, so that it can be reviewed later.

[0947] Step 11:

[0948] Users can check the sending logs as needed to evaluate whether notifications were delivered successfully. The logs contain detailed records of the sending status of each email.

[0949] In this way, the system efficiently performs a series of processes, from acquiring customer information to generating customized notification content, analyzing sentiment data, and sending emails, enabling it to respond in a way that takes user emotions into consideration.

[0950] (Example 2)

[0951] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0952] In modern corporate sales, it is crucial to streamline communication with customers while generating customized notifications tailored to individual customer needs. However, while traditional systems could generate automated notifications based on customer information, they did not further customize the notification content to consider user emotions. As a result, customers received standardized messages, and it was difficult to respond in a way that took individual circumstances and emotions into account. Furthermore, the manual process of selecting templates and customizing notification content was also inefficient.

[0953] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for selecting a template for notifying customers of various information based on customer information obtained from a database, means for analyzing the obtained customer information and user sentiment data to select the optimal template, means for using artificial intelligence to generate customized notification content based on the selected template, and means for sending the generated notification content to the customer. This makes it possible to generate more personalized notification content based on the user's sentiment, thereby improving customer satisfaction. Furthermore, automated template selection and notification content generation can improve operational efficiency.

[0954] A "database" is a computer system that systematically stores information and data, making it searchable and retrievable.

[0955] "Customer information" refers to data about a customer, including information such as delivery status, schedule, and activation status.

[0956] A "template" is a pre-configured document or format tailored to a specific purpose, and it forms the basis of the notification content.

[0957] "User emotion data" refers to data related to emotions analyzed from the user's facial expressions, voice, or text input.

[0958] "Analysis" is the process of examining data and information in detail to find patterns, trends, and relationships within them.

[0959] "Artificial intelligence" is a technology that enables machines to learn, make decisions, and solve problems like humans, and in this invention, it is used to generate customized notification content.

[0960] "Notification content" refers to the information and messages that should be conveyed to the customer, and is customized based on templates and sentiment data.

[0961] "Transmission" refers to the act of delivering information or data to another system or user through a computer system.

[0962] The system of this invention is designed to streamline communication with customers in corporate sales and to automatically generate and send customized notification content based on the user's emotions to the customer. The main components of the system include a database, a template selection means, artificial intelligence for generating customized notification content, means for sending the notification content to the customer, and an emotion engine.

[0963] Specific processing of the program

[0964] The system processes are structured as follows:

[0965] 1. User requests and data acquisition

[0966] A user requests updates regarding specific customer information via their device. The user enters the customer ID into the device and sends a data retrieval request to the server. The server retrieves the relevant customer information (delivery status, schedule, activation status, etc.) from the database.

[0967] 2. Emotion recognition

[0968] The device transmits the user's facial expressions, voice, and text input to the emotion engine in real time. The emotion engine analyzes this data and recognizes the emotions the user is feeling (e.g., anxiety, joy). This emotion data is sent to a server and stored there.

[0969] 3. Template Selection

[0970] The server analyzes the acquired customer information and sentiment data to select a notification template. The server uses rule-based algorithms or machine learning models to choose the best one from several pre-configured email templates.

[0971] 4. Generating customized emails

[0972] The server uses its AI Writer function to generate customized notification content based on the selected template, acquired data, and sentiment data. Specifically, it replaces placeholders within the template with dynamic data and sentiment-based content.

[0973] 5. Send email

[0974] The server uses an SMTP server to send the generated customized notification content to the specified customer email address. After sending, the server records the sending result and saves it to a log file or database for later review.

[0975] Hardware and software to be used

[0976] Database: A database system for storing and managing customer information (delivery status, schedule, activation status, etc.).

[0977] Template selection method: Program logic or algorithm executed within the server.

[0978] Artificial intelligence: AI modules for generating customized notification content (e.g., AI Writer).

[0979] Emotion Engine: A software module equipped with facial recognition and speech analysis capabilities.

[0980] SMTP server: A mail sending server used to send notification content to customers.

[0981] Specific example

[0982] The following describes how to handle a situation where a delivery to customer "12345" is delayed and the user is feeling anxious about the situation.

[0983] 1. User requests and data acquisition

[0984] The user enters customer ID "12345" into the terminal and sends a data retrieval request to the server.

[0985] The server retrieves customer delivery status, schedule, and activation status from the database.

[0986] 2. Emotion recognition

[0987] The device transmits the user's facial expressions and voice to the emotion engine, which recognizes that the user is feeling anxious.

[0988] 3. Template Selection

[0989] The server analyzes the acquired data and sentiment data, selects a "delayed notification template," and then adds "content that provides a sense of relief."

[0990] 4. Generating customized emails

[0991] The server uses an AI Writer to generate customized notification content.

[0992] Example: "Customer, there is a delay in the delivery of product ID: 12345. We will contact you shortly with the new delivery date. We apologize for any inconvenience this may cause. Please contact us if you have any questions or concerns."

[0993] 5. Send email

[0994] The server sends the generated email to the customer "customer@example.com" and records the sending log.

[0995] Example of a prompt

[0996] Prompt: "Generate a customized email to reassure a customer whose delivery is delayed. The customer ID is 12345."

[0997] Expected output example:

[0998] "Dear customer, there is a delay in the delivery of product ID: 12345. We will contact you shortly with the new delivery date. We apologize for any inconvenience this may cause. Please contact us if you have any questions or concerns."

[0999] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1000] Processing flow

[1001] Step 1:

[1002] A user requests updates regarding specific customer information via their device. Specifically, the user logs into the device, enters the customer ID, and clicks the "Get Data" button. This action causes the device to send a data retrieval request, including the customer ID, to the server. The input is the customer ID, and the output is a request message containing the data retrieval request. The server receives the request and creates and executes a database query.

[1003] Step 2:

[1004] The server queries the database to retrieve customer information. This process uses the customer ID submitted as input to retrieve information such as the customer's delivery status, schedule, and activation status from the database. Specifically, an SQL query like "SELECT FROM customer_information WHERE customer_ID = '12345'" is executed. The output is a customer_information dataset as the query result.

[1005] Step 3:

[1006] The device captures the user's facial expressions, voice, and text input in real time. The device sends the captured data to an emotion engine, which analyzes it to generate the user's emotion data. The input consists of the user's facial image and voice data, which are processed by facial recognition algorithms and voice analysis algorithms. The output is the analyzed emotion data (e.g., anxiety, joy).

[1007] Step 4:

[1008] The server selects the most suitable template based on the acquired customer information and sentiment data. The server uses a rule-based algorithm or machine learning model to select the appropriate template from its template storage. The input is the acquired customer information and sentiment data, and the output is the selected notification template. For example, if a customer's delivery is delayed and the user is feeling anxious, the "delay notification template" will be selected.

[1009] Step 5:

[1010] The server generates customized notification content based on the selected template, acquired data, and sentiment data. Specifically, the AI ​​Writer function replaces placeholders in the template with dynamic data and sentiment-based content. The input is the selected template, customer information, and sentiment data, and the output is the generated customized notification content. For example, an email message like, "Dear customer, there is a delay in the delivery of product ID: 12345. We will contact you shortly with the new delivery date. We apologize for any inconvenience this may cause. Please contact us if you have any questions or concerns," is generated.

[1011] Step 6:

[1012] The server sends the generated customized notification content to the specified customer email address using an SMTP server. The inputs are the generated notification content and the customer's email address, and the output is the sent email and its result. This process includes connecting to the SMTP server, establishing an email sending session, sending the email content, and recording the sending log. After sending is complete, the sending log is recorded on the server for later review.

[1013] This allows the system to efficiently notify customers and provide customized notification content that takes user emotions into consideration.

[1014] (Application Example 2)

[1015] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1016] Conventional customer information notification systems have difficulty accurately reflecting customers' real-time emotions and intentions in their communication, resulting in problems such as decreased customer satisfaction and reduced sales efficiency. Furthermore, notification content based on standard templates lacks individualized attention to customers, potentially leading to missed business opportunities.

[1017] In Application Example 2, the specific processing performed by the specific processing unit 290 of the data processing device 12 is realized by the following means. In this invention, the server includes means for selecting a template for notifying customers of various information based on customer information obtained from a database, means for generating customized notification content based on the template, means for sending the generated notification content to the customer, and means for analyzing the user's emotions using an emotion recognition device and further customizing the notification content based on the results. This enables highly accurate customer service in real time, improving customer satisfaction and sales efficiency.

[1018] A "database" is an information management system that stores customer information and allows it to be searched and retrieved as needed.

[1019] A "template selection mechanism" is a means that has the function of automatically selecting an appropriate notification template based on customer information.

[1020] "Means for generating customized notification content" refers to methods for creating individually tailored notification content based on selected templates and customer data.

[1021] "Means for sending notification content to customers" refers to means that have the function of sending the generated notification content to customers.

[1022] An "emotion recognition device" is a device or software that analyzes a user's emotions from their facial expressions, voice, etc., and recognizes a specific emotional state.

[1023] "Visit history" refers to information about a customer's history of visiting a store, including the date, time, and frequency of visits.

[1024] "Purchase history" refers to a record of information about products and services that a customer has purchased in the past.

[1025] "Facial expression" refers to the emotional state indicated by the movement of a customer's facial muscles.

[1026] "Voice" refers to an audio signal used to recognize an emotional state by analyzing the customer's voice characteristics, such as tone, pitch, and speed.

[1027] "Artificial intelligence" refers to computer algorithms or software that learn from large amounts of data and automatically perform specific tasks.

[1028] A "generative AI model" is a model that uses artificial intelligence technology to automatically generate content from input data.

[1029] "Real-time" refers to a state where processing and responses occur almost immediately after an event takes place, with virtually no delay.

[1030] A description of an embodiment for carrying out this invention will be provided. This system performs customer information acquisition, sentiment recognition, template selection, customized notification generation, and notification transmission in a series of steps.

[1031] Hardware and software to be used

[1032] hardware

[1033] Smartphones: Used by store staff, they function as input devices for acquiring customer information and recognizing emotions.

[1034] Server: The central hardware that performs data processing and runs AI models.

[1035] software

[1036] Database: Stores and manages customer information (visit history, purchase history, etc.).

[1037] EmotionEngine: Software that analyzes and recognizes emotions from the user's facial expressions and voice.

[1038] TemplateSelector: Software that selects the appropriate template based on customer information and sentiment data.

[1039] AIWriter: An artificial intelligence model that generates customized notification content based on analysis results.

[1040] SMTP server: A mail server used to send generated notification content to customers.

[1041] Data processing and data calculation workflow

[1042] 1. Data Acquisition

[1043] The server retrieves customer information (visit history, purchase history, etc.) from the database. The user (employee) enters the customer ID into their smartphone and sends a data retrieval request to the server. The server accesses the database and retrieves the necessary information.

[1044] 2. Emotion recognition

[1045] Users interact with customers via their smartphones and capture their facial expressions with the camera. The smartphones send this data to an emotion recognition device called EmotionEngine, which analyzes and recognizes emotional data. For example, it can identify emotions such as "dissatisfaction" or "reassurance" from facial expressions and tone of voice.

[1046] 3. Template Selection

[1047] The server uses TemplateSelector to choose an appropriate template based on the acquired customer information and analyzed sentiment data. This template is the basic text for efficiently structuring notification content.

[1048] 4. Generate customized notifications

[1049] The server uses AIWriter to customize the selected template based on customer information and sentiment data. The generated notification content is tailored to each customer.

[1050] 5. Send Notification

[1051] The server sends the generated customized notification content to the customer using an SMTP server. After sending, a transmission log is recorded for later review.

[1052] Specific example

[1053] scenario

[1054] Customer "Customer ID: 54321" enters the store. A store employee uses a smartphone app to retrieve customer information. Based on the customer's facial expression, it is determined that the customer is dissatisfied with the waiting time.

[1055] Prompts for Generative AI Models

[1056] Please retrieve the information for customer ID: 54321.

[1057] We recognized that the customer was dissatisfied.

[1058] Choose an appropriate template and create a customized notification that includes reassuring content.

[1059] This will allow for more efficient and effective customer service in physical stores, leading to improved customer satisfaction and increased operational efficiency.

[1060] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1061] Step 1:

[1062] The user enters their customer ID using their smartphone and sends a data retrieval request to the server. The server retrieves customer information corresponding to the entered customer ID from the database and responds. The input is the customer ID, and the output is the corresponding customer information (visit history, purchase history, etc.).

[1063] Step 2:

[1064] The terminal interacts with the customer and captures their facial expressions using its camera, sending the collected data to the EmotionEngine, an emotion recognition device. The EmotionEngine analyzes this data and outputs the customer's emotional data (e.g., dissatisfaction, relief, etc.). The input is emotional input data such as facial expressions and voice, and the output is the recognized emotional data.

[1065] Step 3:

[1066] The server uses TemplateSelector to choose the optimal template based on the acquired customer information and emotion data from EmotionEngine. In this process, the server determines the template considering the customer's state and emotions. The input is customer information and emotion data, and the output is the selected template.

[1067] Step 4:

[1068] The server sends the selected template, retrieved customer information, and sentiment data to the AIWriter to generate customized notification content. The AIWriter uses this information to replace the template's placeholders with dynamic data and sentiment-based content. The inputs are the template, customer information, and sentiment data, while the output is the customized notification content.

[1069] Step 5:

[1070] The server sends the generated customized notification content to the customer using an SMTP server. After the email is delivered to the customer via the SMTP server, a transmission log is recorded for later review. The input is the customized notification content, and the output is the transmission log and delivery to the customer.

[1071] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1072] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1073] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[1074] [Fourth Embodiment]

[1075] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1076] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1077] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1078] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[1079] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[1080] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[1081] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[1082] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[1083] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[1084] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1085] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1086] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[1087] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1088] System Embodiment

[1089] This invention relates to a system that streamlines customer notification operations in corporate sales and automatically generates and sends individually customized notification content. The system consists of the following main components:

[1090] Database for obtaining customer information

[1091] Means for selecting an appropriate template

[1092] Artificial intelligence for generating customized notification content

[1093] Means for sending notification content to customers

[1094] Program processing

[1095] 1. Data Acquisition

[1096] When a user needs to update information related to a specific customer, they send a request to the server via their terminal. The server retrieves the relevant customer information from the database, namely delivery status, schedule, and activation status. For example, to retrieve information for customer ID "12345", the server retrieves the relevant data from the database via a query.

[1097] 2. Template Selection

[1098] The server analyzes the acquired data and selects the template best suited to the customer's situation. For example, if delivery is delayed, a delay notification template is selected. Different templates are chosen depending on whether the delivery is on schedule or for other reasons.

[1099] 3. Generate customized emails

[1100] The server uses the AI ​​Writer extension to generate customized notification content based on the selected template and retrieved data. Specifically, it replaces placeholders in the template with dynamic data to generate individually customized email bodies.

[1101] 4. Send email

[1102] After reviewing the generated email content, the server sends the email to the customer's email address via the SMTP server. During sending, a transmission log is recorded, and information such as the success or failure of the transmission and the time of transmission is stored.

[1103] Specific example

[1104] Let's take the example of a case where delivery to customer "12345" is delayed. In this case, the process proceeds as follows:

[1105] 1. The terminal enters customer ID "12345" and sends a data retrieval request to the server.

[1106] 2. The server retrieves the delivery status, schedule, and activation status of the relevant customer from the database.

[1107] 3. The server analyzes the acquired data and, because a delivery delay has occurred, selects a delay notification template.

[1108] 4. The server generates customized notification content using AI Writer based on templates and data.

[1109] Example: "We sincerely apologize, but the delivery of product ID: 12345 is delayed. We will contact you later with the new delivery date."

[1110] 5. The server sends the generated email to "customer@example.com".

[1111] In this way, this system streamlines customer notification operations for corporate sales departments and enables the rapid delivery of customized notifications to individual customers.

[1112] The following describes the processing flow.

[1113] Step 1:

[1114] A user requests to view or send updated information about a specific customer via their device. The user uses a GUI to enter the relevant customer ID and triggers a data retrieval request.

[1115] Step 2:

[1116] The device sends the user's request to the server as an API request. The request includes the customer ID and the necessary information.

[1117] Step 3:

[1118] The server receives the request and sends a query to the database based on the specified customer ID. The server retrieves customer information, including delivery status, schedule, and activation status.

[1119] Step 4:

[1120] The server analyzes customer information retrieved from the database and selects a template appropriate to the situation. For example, if delivery is delayed, a delay notification template will be selected.

[1121] Step 5:

[1122] The server loads a selected template and generates customized notification content using an AI Writer extension based on customer information. The template's placeholders are replaced with dynamic data, creating individually customized email content.

[1123] Step 6:

[1124] The server passes the generated notification content to the SMTP server, which then sends an email to the customer's email address. The outgoing email contains dynamically generated customized content.

[1125] Step 7:

[1126] The server records email sending logs. It saves information such as whether the email was sent successfully or not, and the time of sending, to facilitate later review and troubleshooting.

[1127] Step 8:

[1128] Users can check the sending logs as needed to evaluate whether notifications were delivered successfully. The logs contain detailed records of the sending status of each email.

[1129] These steps enable the system to perform customer notification tasks efficiently and effectively, and to quickly deliver customized notifications to individual customers.

[1130] (Example 1)

[1131] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1132] In corporate sales, customer notification tasks require the rapid generation and efficient transmission of individually customized notification content. Traditional manual notification methods are time-consuming, labor-intensive, and prone to human error. Furthermore, selecting and customizing templates to suit diverse customer situations is difficult, making them unsuitable for today's business environment where quick and accurate responses are essential.

[1133] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1134] In this invention, the server includes means for obtaining specific customer information based on a request received from a device, means for obtaining customer information from a database using queries, means for analyzing the obtained customer information and selecting an appropriate template, means for generating customized notification content using an artificial intelligence model based on the selected template and obtained data, means for sending the generated notification content to the customer, and means for recording a transmission log. This makes it possible to automate customer notification operations and provide customized notification content quickly and accurately.

[1135] A "device" is an input device that sends a request to retrieve customer information to a server, or a device that has that function.

[1136] A "request" is data that a device sends to a server to request specific customer information.

[1137] A "server" is a central processing unit that acquires, analyzes, generates, and transmits customer information.

[1138] A "database" is a data storage system that manages and stores customer information.

[1139] A "query" is a command or question that is executed against a database to retrieve specific information.

[1140] "Customer information" refers to data related to a customer, including information such as shipping status, schedule, and connection status.

[1141] A "template" is a format for describing notification content, and it includes placeholders that are appropriate for specific situations.

[1142] An "artificial intelligence model" is an algorithm or program that uses machine learning or deep learning techniques to generate customized notification content.

[1143] "Notification content" refers to the message sent to the customer, generated based on a template and customer information.

[1144] "Transmission means" refers to the means of communication used to send the generated notification content to the customer.

[1145] A "transmission log" records data such as the success or failure of sending notification content, and the time of transmission.

[1146] System Embodiment

[1147] This invention relates to a system that streamlines customer notification operations in corporate sales and automatically generates and sends individually customized notification content. The system consists of the following main components:

[1148] Database for obtaining customer information

[1149] Means for selecting an appropriate template

[1150] Artificial intelligence model for generating customized notification content

[1151] Means for sending notification content to customers

[1152] Program processing

[1153] Data acquisition

[1154] When a user needs to update information related to a specific customer, they send a request to the server via their terminal. The server retrieves the relevant customer information from the database. For example, to retrieve information for customer ID "12345", the server executes an SQL query to obtain the customer's delivery status, schedule, and connection status.

[1155] Template Selection

[1156] The server analyzes the acquired data and selects the template best suited to the customer's situation. For example, if delivery is delayed, a delay notification template will be selected. Different templates are selected depending on whether the delivery is on schedule or for other reasons.

[1157] Custom email generation

[1158] The server uses an artificial intelligence model (e.g., OpenAI's GPT-3) based on the selected template and acquired data to generate customized notification content. Specifically, it replaces placeholders in the template with dynamic data to generate individually customized email bodies.

[1159] Examples of prompt statements are as follows:

[1160] "Please use the following template to generate a customized email regarding a delivery delay for customer ID "12345". Template: Dear {{customer_name}}, We hope this email finds you well. The delivery of product ID: {{product_id}} is delayed. We will contact you later with the new delivery date. Customer data: { "customer_name": "Taro Yamada", "product_id": "XYZ123"}"

[1161] Send email

[1162] After reviewing the generated email content, the server sends the email to the customer's email address via an SMTP server (e.g., Postfix). During sending, a transmission log is recorded, and information such as success or failure of transmission and the time of transmission is stored.

[1163] Specific example

[1164] Let's take the example of a case where the delivery for customer ID "12345" is delayed. In this case, the process proceeds as follows:

[1165] 1. The user enters customer ID "12345" on their terminal and sends a data retrieval request to the server.

[1166] 2. The server retrieves the delivery status, schedule, and connection status of the relevant customer from the database.

[1167] 3. The server analyzes the acquired data and, because a delivery delay has occurred, selects a delay notification template.

[1168] 4. The server generates customized notification content using an AI model based on templates and data.

[1169] Example: "We sincerely apologize, but the delivery of product ID: 12345 is delayed. We will contact you later with the new delivery date."

[1170] 5. The server sends the generated email to the customer's email address.

[1171] In this way, this system streamlines customer notification operations for corporate sales departments and enables the rapid delivery of customized notifications to individual customers.

[1172] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1173] Step 1:

[1174] The user enters a customer information update request on their terminal. This includes entering the customer ID (e.g., 12345) and other necessary information into the input form. When the user clicks the "Submit" button, the information is sent to the server as an HTTP request.

[1175] Input: Customer ID, Request Details

[1176] Output: Sending requested data

[1177] Step 2:

[1178] The server parses the received request data. The server extracts the customer ID from the request data, generates an SQL query to retrieve the corresponding customer information from the database (e.g., MySQL), and executes it. A specific query might be something like "SELECT FROM customers WHERE customer_id = '12345'" and retrieves the results.

[1179] Input: Request data (Customer ID)

[1180] Output: Retrieval of customer information data

[1181] Step 3:

[1182] The server analyzes the acquired customer information data. This analysis is performed using, for example, the Pandas library. The server analyzes information such as the customer's delivery status, schedule, and connection status to determine which template is appropriate. Based on this information, it selects the appropriate template (for example, a delay notification template).

[1183] Input: Customer information data

[1184] Output: Selected template

[1185] Step 4:

[1186] The server uses the selected template and analyzed customer information to send a prompt to a generating AI model (e.g., OpenAI's GPT-3) to generate customized notification content. A prompt might include, "Please use the following template to generate a customized email for when the delivery of customer ID "12345" is delayed." The AI ​​model then generates specific notification content (e.g., "Mr. / Ms. Yamada, we sincerely apologize, but the delivery of product ID: 12345 is delayed.").

[1187] Input: Selected template, customer information

[1188] Output: Customized notification content

[1189] Step 5:

[1190] The server sends the generated notification content to the customer's email address via an SMTP server (e.g., Postfix). The server establishes an SMTP connection and sends the notification content to the customer's email address according to the email sending protocol. After sending is complete, the server records information such as success / failure and sending time in the sending log.

[1191] Input: Customized notification content, customer's email address

[1192] Output: Transmission results, transmission log recording

[1193] By following these steps, this system can quickly and accurately generate and send customized customer notification content.

[1194] (Application Example 1)

[1195] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1196] In today's food delivery industry, the various notification tasks for customers are extremely diverse and difficult to perform efficiently. While it is necessary to quickly notify each customer of their delivery status, estimated arrival time, and delivery person information, customizing the content of these notifications individually is time-consuming. Furthermore, delays in selecting appropriate templates for situations such as delivery delays or special offers can lead to decreased customer satisfaction and reduced operational efficiency.

[1197] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1198] In this invention, the server includes means for selecting a template for notifying customers of various information based on customer information obtained from a database, means for generating customized notification content based on the template, communication means for sending the generated notification content to the customer, and means for sending the notification content in push notification format on various devices. This makes it possible to quickly generate and send individually customized notification content.

[1199] A "database" is an electronic system for systematically organizing information and efficiently searching, updating, and managing it.

[1200] "Customer information" refers to data about the customer, including name, contact information, delivery status, estimated arrival time, and delivery person information.

[1201] A "template" is a document model with a specific format and structure, and serves as a basic framework for automatically generating notification content.

[1202] "Customized notification content" refers to notification messages that are individually tailored based on the specific circumstances and information of a particular customer.

[1203] "Means of generation" refers to devices or programs that have the ability or function to perform a specific process and produce a desired output result.

[1204] "Communication methods" refer to means of sending information to specific recipients, and include email and push notifications.

[1205] "Push notifications" are a notification format that sends information to the user in real time and displays it immediately on the device screen.

[1206] "Delivery status" refers to status information that indicates the stage of delivery for an ordered item in a food delivery service.

[1207] "Estimated arrival time" refers to information indicating the time when a particular delivery is expected to arrive at the designated recipient's location.

[1208] "Delivery driver information" refers to information about the employee responsible for delivery, including their name, contact information, and delivery history.

[1209] A "generative AI model" is an algorithm or data model that uses artificial intelligence to process data and generate output tailored to a specific task or purpose.

[1210] The system for realizing this invention automatically generates and sends individually customized notification content based on customer information obtained from a database. This system consists of the following main components.

[1211] System components

[1212] 1. Database

[1213] A database is an electronic system for systematically organizing customer information and efficiently searching, updating, and managing it. Specifically, it stores customer delivery status, estimated arrival time, and delivery person information.

[1214] 2. Server

[1215] The server retrieves customer information from the database, analyzes that information, and selects the optimal template. Furthermore, it uses a generative AI model to generate customized notification content based on the selected template.

[1216] 3. Means of communication

[1217] The server has communication means to send the generated notification content to various devices. This includes email and push notifications.

[1218] 4. Terminal

[1219] The terminals are devices used by customers and delivery personnel, and include smartphones and tablets. These terminals display information sent as push notifications in real time.

[1220] Program processing

[1221] The server runs using Python and programs such as Flask. It uses sqlite3 for database connections and smtplib for sending emails. OpenAI GPT-3 is used for the generative AI model.

[1222] First, the user sends a request from their device to the server to review or update information related to a specific customer. The server retrieves the customer information from the database, analyzes it, and selects an appropriate notification template. Next, it uses a generative AI model to generate customized notification content based on the template. This notification content includes information such as the customer name, order ID, scheduled arrival time, and new estimated arrival time.

[1223] The generated notification content is sent to various devices via communication means. For example, if it is sent as a push notification to a smartphone, the customer can immediately check the delivery status. The sent notification log is recorded, and information such as the success or failure of the transmission and the time of transmission is stored.

[1224] Specific example

[1225] Here are some specific examples of how customers use food delivery services.

[1226] 1. The user sends a request from their device to the server to check the delivery status.

[1227] 2. The server retrieves the relevant customer information from the database and recognizes that a delivery delay has occurred.

[1228] 3. The server selects a delayed notification template and uses a generation AI model to generate customized notification content.

[1229] 4. The generated notification reads: "We sincerely apologize, but the delivery of your ordered item ID: ABC123 is delayed. The new estimated arrival time is 14:30."

[1230] 5. This notification content will be sent to the smartphone as a push notification via a communication method.

[1231] Example of a prompt

[1232] "Use the generation AI model to generate a delivery delay notification for customer 'Yamada Taro' with order ID 'XYZ789'. The estimated arrival time is '15:00'."

[1233] In this way, the present invention is a system that can streamline customer notification operations in the food delivery industry and improve customer satisfaction.

[1234] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1235] Step 1:

[1236] The user uses a terminal to check or update the delivery status and sends a request to the server. The input is the customer ID and the type of information to be checked, and the output is the request data sent to the server. Once the request is sent, the server receives the data and proceeds to the next step.

[1237] Step 2:

[1238] The server queries the database based on the received request. The input is the customer ID and related request information, and the output is data retrieved from the database, such as the customer's delivery status, estimated arrival time, and delivery person information. The server retrieves the relevant data from the database and prepares it for analysis.

[1239] Step 3:

[1240] The server analyzes the retrieved customer information and selects a template appropriate to the customer's situation. The input is customer information retrieved from the database, and the output is the selected template. For example, if a delivery is delayed, a delay notification template will be selected.

[1241] Step 4:

[1242] The server generates customized notification content using a generative AI model based on the selected template and retrieved data. The input is the template and customer information, and the output is a specific notification message. Specifically, the AI ​​model inserts the customer's specific data into placeholders within the template to generate the final notification content.

[1243] Step 5:

[1244] The server reviews the generated notification content and sends it to the customer via a communication method. The input is the generated notification message, and the output is the notification sent to various devices. Specifically, the server either sends an email using an SMTP server or sends a real-time notification to a smartphone using a push notification system.

[1245] Step 6:

[1246] The server logs sent notifications, saving information such as success, failure, and transmission time. Input is the status information of the transmission result, and output is the transmission history stored in log files or a database. This enables troubleshooting and history auditing.

[1247] This entire processing step allows users to track the delivery status in real time and receive personalized notifications quickly.

[1248] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1249] System Embodiment

[1250] This invention relates to a system that streamlines customer communication in corporate sales, automatically generates customized notification content, and further customizes it based on user sentiment. The main components of the system include the following:

[1251] database

[1252] Template selection method

[1253] Artificial intelligence that generates customized notification content

[1254] Means of sending notification content to customers

[1255] Emotional Engine

[1256] Program processing

[1257] 1. User requests and data acquisition

[1258] A user requests updates regarding specific customer information via their device. The user enters the customer ID and sends a data retrieval request to the server. The server retrieves the customer information from the database. This information includes delivery status, schedule, and activation status.

[1259] 2. Emotion recognition

[1260] The device sends the user's facial expressions, voice, or text input to the emotion engine. The emotion engine analyzes this data to recognize the user's emotions. For example, if it determines that the user is feeling anxious, it customizes the notification content based on that information.

[1261] 3. Template Selection

[1262] The server analyzes the acquired customer information and sentiment data obtained from the sentiment engine, and selects an appropriate template based on this analysis. For example, if the sentiment engine determines that the user is anxious, it will select a template that provides a greater sense of reassurance.

[1263] 4. Generating customized emails

[1264] The server uses the AI ​​Writer extension to generate customized notification content based on the selected template, acquired data, and sentiment data. Specifically, it replaces placeholders within the template with dynamic data and sentiment-based content.

[1265] 5. Send email

[1266] The server sends the generated customized notification content to the customer using an SMTP server. After the transmission is complete, a transmission log is recorded for later review.

[1267] Specific example

[1268] Let's take the example of how to handle a situation where a delivery to customer "12345" is delayed, and the user is feeling anxious about this situation.

[1269] 1. The terminal enters customer ID "12345" and sends a data retrieval request to the server.

[1270] 2. The server retrieves customer delivery status, schedule, and activation status from the database.

[1271] 3. Simultaneously, the device transmits the user's facial expressions and voice to the emotion engine, which recognizes that the user is feeling anxious.

[1272] 4. The server analyzes the acquired data and sentiment data, selects a "delayed notification template," and then adds "content that provides a sense of relief."

[1273] 5. The server uses an AI Writer to generate customized notification content.

[1274] Example: "Customer, there is a delay in the delivery of product ID: 12345. We will contact you shortly with the new delivery date. We apologize for any inconvenience this may cause. Please contact us if you have any questions or concerns."

[1275] 6. The server sends the generated email to the customer "customer@example.com" and records the sending log.

[1276] These processes enable efficient customer notifications and allow for customization based on user emotions, which is expected to improve operational efficiency and customer satisfaction.

[1277] The following describes the processing flow.

[1278] Step 1:

[1279] The user requests an update to customer information via their device. Specifically, the user enters a specific customer ID in the GUI and clicks the "Get Data" button.

[1280] Step 2:

[1281] The device sends the user's request to the server as an API request. The request includes the specified customer ID.

[1282] Step 3:

[1283] The server receives the API request and sends a query to the database based on the specified customer ID. For example, it retrieves the delivery status, schedule, and activation status for customer ID "12345".

[1284] Step 4:

[1285] The server analyzes customer information retrieved from the database. For example, it checks whether deliveries are delayed or whether the schedule is on track.

[1286] Step 5:

[1287] The device collects data to recognize the user's emotions. Specifically, it captures facial expressions with the device's camera, collects voice tone with the microphone, and analyzes text input.

[1288] Step 6:

[1289] The device sends collected emotional data to the emotion engine. The emotion engine analyzes this data and recognizes the user's emotions. For example, it might determine that the user is feeling anxious.

[1290] Step 7:

[1291] The server selects a template based on customer information and sentiment data it has acquired. If delivery is delayed, it selects a delay notification template, and if the user is feeling anxious, it selects a template that includes content to provide reassurance.

[1292] Step 8:

[1293] The server loads a selected template and uses the AI ​​Writer extension to customize the notification content. For example, it generates emails that include messages such as "Delivery is delayed," "New deadline announcement," and "Message to alleviate concerns."

[1294] Step 9:

[1295] The server verifies the generated customized email content and sends it to the customer's email address via the SMTP server. For example, it sends an email to "customer@example.com".

[1296] Step 10:

[1297] The server records transmission logs. It saves information such as whether the transmission was successful or unsuccessful, and the transmission time, so that it can be reviewed later.

[1298] Step 11:

[1299] Users can check the sending logs as needed to evaluate whether notifications were delivered successfully. The logs contain detailed records of the sending status of each email.

[1300] In this way, the system efficiently performs a series of processes, from acquiring customer information to generating customized notification content, analyzing sentiment data, and sending emails, enabling it to respond in a way that takes user emotions into consideration.

[1301] (Example 2)

[1302] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1303] In modern corporate sales, it is crucial to streamline communication with customers while generating customized notifications tailored to individual customer needs. However, while traditional systems could generate automated notifications based on customer information, they did not further customize the notification content to consider user emotions. As a result, customers received standardized messages, and it was difficult to respond in a way that took individual circumstances and emotions into account. Furthermore, the manual process of selecting templates and customizing notification content was also inefficient.

[1304] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for selecting a template for notifying customers of various information based on customer information obtained from a database, means for analyzing the obtained customer information and user sentiment data to select the optimal template, means for using artificial intelligence to generate customized notification content based on the selected template, and means for sending the generated notification content to the customer. This makes it possible to generate more personalized notification content based on the user's sentiment, thereby improving customer satisfaction. Furthermore, automated template selection and notification content generation can improve operational efficiency.

[1305] A "database" is a computer system that systematically stores information and data, making it searchable and retrievable.

[1306] "Customer information" refers to data about a customer, including information such as delivery status, schedule, and activation status.

[1307] A "template" is a pre-configured document or format tailored to a specific purpose, and it forms the basis of the notification content.

[1308] "User emotion data" refers to data related to emotions analyzed from the user's facial expressions, voice, or text input.

[1309] "Analysis" is the process of examining data and information in detail to find patterns, trends, and relationships within them.

[1310] "Artificial intelligence" is a technology that enables machines to learn, make decisions, and solve problems like humans, and in this invention, it is used to generate customized notification content.

[1311] "Notification content" refers to the information and messages that should be conveyed to the customer, and is customized based on templates and sentiment data.

[1312] "Transmission" refers to the act of delivering information or data to another system or user through a computer system.

[1313] The system of this invention is designed to streamline communication with customers in corporate sales and to automatically generate and send customized notification content based on the user's emotions to the customer. The main components of the system include a database, a template selection means, artificial intelligence for generating customized notification content, means for sending the notification content to the customer, and an emotion engine.

[1314] Specific processing of the program

[1315] The system processes are structured as follows:

[1316] 1. User requests and data acquisition

[1317] A user requests updates regarding specific customer information via their device. The user enters the customer ID into the device and sends a data retrieval request to the server. The server retrieves the relevant customer information (delivery status, schedule, activation status, etc.) from the database.

[1318] 2. Emotion recognition

[1319] The device transmits the user's facial expressions, voice, and text input to the emotion engine in real time. The emotion engine analyzes this data and recognizes the emotions the user is feeling (e.g., anxiety, joy). This emotion data is sent to a server and stored there.

[1320] 3. Template Selection

[1321] The server analyzes the acquired customer information and sentiment data to select a notification template. The server uses rule-based algorithms or machine learning models to choose the best one from several pre-configured email templates.

[1322] 4. Generating customized emails

[1323] The server uses its AI Writer function to generate customized notification content based on the selected template, acquired data, and sentiment data. Specifically, it replaces placeholders within the template with dynamic data and sentiment-based content.

[1324] 5. Send email

[1325] The server uses an SMTP server to send the generated customized notification content to the specified customer email address. After sending, the server records the sending result and saves it to a log file or database for later review.

[1326] Hardware and software to be used

[1327] Database: A database system for storing and managing customer information (delivery status, schedule, activation status, etc.).

[1328] Template selection method: Program logic or algorithm executed within the server.

[1329] Artificial intelligence: AI modules for generating customized notification content (e.g., AI Writer).

[1330] Emotion Engine: A software module equipped with facial recognition and speech analysis capabilities.

[1331] SMTP server: A mail sending server used to send notification content to customers.

[1332] Specific example

[1333] The following describes how to handle a situation where a delivery to customer "12345" is delayed and the user is feeling anxious about the situation.

[1334] 1. User requests and data acquisition

[1335] The user enters customer ID "12345" into the terminal and sends a data retrieval request to the server.

[1336] The server retrieves customer delivery status, schedule, and activation status from the database.

[1337] 2. Emotion recognition

[1338] The device transmits the user's facial expressions and voice to the emotion engine, which recognizes that the user is feeling anxious.

[1339] 3. Template Selection

[1340] The server analyzes the acquired data and sentiment data, selects a "delayed notification template," and then adds "content that provides a sense of relief."

[1341] 4. Generating customized emails

[1342] The server uses an AI Writer to generate customized notification content.

[1343] Example: "Customer, there is a delay in the delivery of product ID: 12345. We will contact you shortly with the new delivery date. We apologize for any inconvenience this may cause. Please contact us if you have any questions or concerns."

[1344] 5. Send email

[1345] The server sends the generated email to the customer "customer@example.com" and records the sending log.

[1346] Example of a prompt

[1347] Prompt: "Generate a customized email to reassure a customer whose delivery is delayed. The customer ID is 12345."

[1348] Expected output example:

[1349] "Dear customer, there is a delay in the delivery of product ID: 12345. We will contact you shortly with the new delivery date. We apologize for any inconvenience this may cause. Please contact us if you have any questions or concerns."

[1350] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1351] Processing flow

[1352] Step 1:

[1353] A user requests updates regarding specific customer information via their device. Specifically, the user logs into the device, enters the customer ID, and clicks the "Get Data" button. This action causes the device to send a data retrieval request, including the customer ID, to the server. The input is the customer ID, and the output is a request message containing the data retrieval request. The server receives the request and creates and executes a database query.

[1354] Step 2:

[1355] The server queries the database to retrieve customer information. This process uses the customer ID submitted as input to retrieve information such as the customer's delivery status, schedule, and activation status from the database. Specifically, an SQL query like "SELECT FROM customer_information WHERE customer_ID = '12345'" is executed. The output is a customer_information dataset as the query result.

[1356] Step 3:

[1357] The device captures the user's facial expressions, voice, and text input in real time. The device sends the captured data to an emotion engine, which analyzes it to generate the user's emotion data. The input consists of the user's facial image and voice data, which are processed by facial recognition algorithms and voice analysis algorithms. The output is the analyzed emotion data (e.g., anxiety, joy).

[1358] Step 4:

[1359] The server selects the most suitable template based on the acquired customer information and sentiment data. The server uses a rule-based algorithm or machine learning model to select the appropriate template from its template storage. The input is the acquired customer information and sentiment data, and the output is the selected notification template. For example, if a customer's delivery is delayed and the user is feeling anxious, the "delay notification template" will be selected.

[1360] Step 5:

[1361] The server generates customized notification content based on the selected template, acquired data, and sentiment data. Specifically, the AI ​​Writer function replaces placeholders in the template with dynamic data and sentiment-based content. The input is the selected template, customer information, and sentiment data, and the output is the generated customized notification content. For example, an email message like, "Dear customer, there is a delay in the delivery of product ID: 12345. We will contact you shortly with the new delivery date. We apologize for any inconvenience this may cause. Please contact us if you have any questions or concerns," is generated.

[1362] Step 6:

[1363] The server sends the generated customized notification content to the specified customer email address using an SMTP server. The inputs are the generated notification content and the customer's email address, and the output is the sent email and its result. This process includes connecting to the SMTP server, establishing an email sending session, sending the email content, and recording the sending log. After sending is complete, the sending log is recorded on the server for later review.

[1364] This allows the system to efficiently notify customers and provide customized notification content that takes user emotions into consideration.

[1365] (Application Example 2)

[1366] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1367] Conventional customer information notification systems have difficulty accurately reflecting customers' real-time emotions and intentions in their communication, resulting in problems such as decreased customer satisfaction and reduced sales efficiency. Furthermore, notification content based on standard templates lacks individualized attention to customers, potentially leading to missed business opportunities.

[1368] In Application Example 2, the specific processing performed by the specific processing unit 290 of the data processing device 12 is realized by the following means. In this invention, the server includes means for selecting a template for notifying customers of various information based on customer information obtained from a database, means for generating customized notification content based on the template, means for sending the generated notification content to the customer, and means for analyzing the user's emotions using an emotion recognition device and further customizing the notification content based on the results. This enables highly accurate customer service in real time, improving customer satisfaction and sales efficiency.

[1369] A "database" is an information management system that stores customer information and allows it to be searched and retrieved as needed.

[1370] A "template selection mechanism" is a means that has the function of automatically selecting an appropriate notification template based on customer information.

[1371] "Means for generating customized notification content" refers to methods for creating individually tailored notification content based on selected templates and customer data.

[1372] "Means for sending notification content to customers" refers to means that have the function of sending the generated notification content to customers.

[1373] An "emotion recognition device" is a device or software that analyzes a user's emotions from their facial expressions, voice, etc., and recognizes a specific emotional state.

[1374] "Visit history" refers to information about a customer's history of visiting a store, including the date, time, and frequency of visits.

[1375] "Purchase history" refers to a record of information about products and services that a customer has purchased in the past.

[1376] "Facial expression" refers to the emotional state indicated by the movement of a customer's facial muscles.

[1377] "Voice" refers to an audio signal used to recognize an emotional state by analyzing the customer's voice characteristics, such as tone, pitch, and speed.

[1378] "Artificial intelligence" refers to computer algorithms or software that learn from large amounts of data and automatically perform specific tasks.

[1379] A "generative AI model" is a model that uses artificial intelligence technology to automatically generate content from input data.

[1380] "Real-time" refers to a state where processing and responses occur almost immediately after an event takes place, with virtually no delay.

[1381] A description of an embodiment for carrying out this invention will be provided. This system performs customer information acquisition, sentiment recognition, template selection, customized notification generation, and notification transmission in a series of steps.

[1382] Hardware and software to be used

[1383] hardware

[1384] Smartphones: Used by store staff, they function as input devices for acquiring customer information and recognizing emotions.

[1385] Server: The central hardware that performs data processing and runs AI models.

[1386] software

[1387] Database: Stores and manages customer information (visit history, purchase history, etc.).

[1388] EmotionEngine: Software that analyzes and recognizes emotions from the user's facial expressions and voice.

[1389] TemplateSelector: Software that selects the appropriate template based on customer information and sentiment data.

[1390] AIWriter: An artificial intelligence model that generates customized notification content based on analysis results.

[1391] SMTP server: A mail server used to send generated notification content to customers.

[1392] Data processing and data calculation workflow

[1393] 1. Data Acquisition

[1394] The server retrieves customer information (visit history, purchase history, etc.) from the database. The user (employee) enters the customer ID into their smartphone and sends a data retrieval request to the server. The server accesses the database and retrieves the necessary information.

[1395] 2. Emotion recognition

[1396] Users interact with customers via their smartphones and capture their facial expressions with the camera. The smartphones send this data to an emotion recognition device called EmotionEngine, which analyzes and recognizes emotional data. For example, it can identify emotions such as "dissatisfaction" or "reassurance" from facial expressions and tone of voice.

[1397] 3. Template Selection

[1398] The server uses TemplateSelector to choose an appropriate template based on the acquired customer information and analyzed sentiment data. This template is the basic text for efficiently structuring notification content.

[1399] 4. Generate customized notifications

[1400] The server uses AIWriter to customize the selected template based on customer information and sentiment data. The generated notification content is tailored to each customer.

[1401] 5. Send Notification

[1402] The server sends the generated customized notification content to the customer using an SMTP server. After sending, a transmission log is recorded for later review.

[1403] Specific example

[1404] scenario

[1405] Customer "Customer ID: 54321" enters the store. A store employee uses a smartphone app to retrieve customer information. Based on the customer's facial expression, it is determined that the customer is dissatisfied with the waiting time.

[1406] Prompts for Generative AI Models

[1407] Please retrieve the information for customer ID: 54321.

[1408] We recognized that the customer was dissatisfied.

[1409] Choose an appropriate template and create a customized notification that includes reassuring content.

[1410] This will allow for more efficient and effective customer service in physical stores, leading to improved customer satisfaction and increased operational efficiency.

[1411] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1412] Step 1:

[1413] The user enters their customer ID using their smartphone and sends a data retrieval request to the server. The server retrieves customer information corresponding to the entered customer ID from the database and responds. The input is the customer ID, and the output is the corresponding customer information (visit history, purchase history, etc.).

[1414] Step 2:

[1415] The terminal interacts with the customer and captures their facial expressions using its camera, sending the collected data to the EmotionEngine, an emotion recognition device. The EmotionEngine analyzes this data and outputs the customer's emotional data (e.g., dissatisfaction, relief, etc.). The input is emotional input data such as facial expressions and voice, and the output is the recognized emotional data.

[1416] Step 3:

[1417] The server uses TemplateSelector to choose the optimal template based on the acquired customer information and emotion data from EmotionEngine. In this process, the server determines the template considering the customer's state and emotions. The input is customer information and emotion data, and the output is the selected template.

[1418] Step 4:

[1419] The server sends the selected template, retrieved customer information, and sentiment data to the AIWriter to generate customized notification content. The AIWriter uses this information to replace the template's placeholders with dynamic data and sentiment-based content. The inputs are the template, customer information, and sentiment data, while the output is the customized notification content.

[1420] Step 5:

[1421] The server sends the generated customized notification content to the customer using an SMTP server. After the email is delivered to the customer via the SMTP server, a transmission log is recorded for later review. The input is the customized notification content, and the output is the transmission log and delivery to the customer.

[1422] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1423] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1424] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[1425] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1426] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[1427] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[1428] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[1429] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[1430] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[1431] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[1432] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[1433] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[1434] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[1435] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1436] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[1437] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[1438] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[1439] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[1440] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[1441] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[1442] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference.

[1443] The following is further disclosed regarding the embodiments described above.

[1444] (Claim 1)

[1445] A means of selecting a template for notifying customers of various information based on customer information obtained from a database,

[1446] A means for generating customized notification content based on the aforementioned template,

[1447] A means of sending the generated notification content to the customer,

[1448] A system that includes this.

[1449] (Claim 2)

[1450] The system according to claim 1, wherein the acquired customer information includes delivery status, schedule, and activation status.

[1451] (Claim 3)

[1452] The system according to claim 1, wherein the means for generating notification content includes means for using artificial intelligence.

[1453] (Claim 4)

[1454] The system according to claim 1, wherein the notification content is in email format.

[1455] (Claim 5)

[1456] The system according to claim 1, comprising means for selecting the template based on conditions.

[1457] (Claim 6)

[1458] The system according to claim 1, wherein the means for obtaining the customer information is performed via an API.

[1459] (Claim 7)

[1460] The system according to claim 1, further comprising means for recording a transmission log of notification content.

[1461] "Example 1"

[1462] (Claim 1)

[1463] A means of obtaining specific customer information based on requests obtained from a device,

[1464] A means of retrieving customer information from a database using queries,

[1465] A means of analyzing acquired customer information and selecting an appropriate template,

[1466] A means of generating customized notification content using an artificial intelligence model based on a selected template and acquired data,

[1467] A means of sending the generated notification content to the customer,

[1468] A means of recording transmission logs,

[1469] A system that includes this.

[1470] (Claim 2)

[1471] The system according to claim 1, wherein acquired customer information includes shipping status, schedule, and connection status.

[1472] (Claim 3)

[1473] The system according to claim 1, wherein the means for generating notification content includes means for using a generation AI model.

[1474] "Application Example 1"

[1475] (Claim 1)

[1476] A means of selecting a template for notifying customers of various information based on customer information obtained from a database,

[1477] A means for generating customized notification content based on the aforementioned template,

[1478] A means of communication for sending the generated notification content to the customer,

[1479] A means for sending the aforementioned notification content in push notification format on various devices,

[1480] A system that includes this.

[1481] (Claim 2)

[1482] The system according to claim 1, wherein the acquired customer information includes delivery status, estimated arrival time, and delivery person information.

[1483] (Claim 3)

[1484] The system according to claim 1, wherein the means for generating notification content includes means for using a generation AI model.

[1485] "Example 2 of combining an emotion engine"

[1486] (Claim 1)

[1487] A means of selecting a template for notifying customers of various information based on customer information obtained from a database,

[1488] A means for analyzing acquired customer information and user sentiment data to select the optimal template,

[1489] A means of using artificial intelligence to generate customized notification content based on a selected template,

[1490] A means of sending the generated notification content to the customer,

[1491] A system that includes this.

[1492] (Claim 2)

[1493] The system according to claim 1, wherein the acquired customer information includes delivery status, schedule, and activation status.

[1494] (Claim 3)

[1495] The system according to claim 1, comprising means for analyzing facial expressions, voice, or text input in order to recognize the user's emotions.

[1496] "Application example 2 when combining with an emotional engine"

[1497] (Claim 1)

[1498] A means of selecting a template for notifying customers of various information based on customer information obtained from a database,

[1499] A means for generating customized notification content based on the aforementioned template,

[1500] A means of sending the generated notification content to the customer,

[1501] A means for analyzing the user's emotions using an emotion recognition device and further customizing the notification content based on the results,

[1502] A system that includes this.

[1503] (Claim 2)

[1504] The system according to claim 1, wherein the acquired customer information includes visit history, purchase history, and the customer's facial expressions and voice.

[1505] (Claim 3)

[1506] The system according to claim 1, wherein the means for generating notification content includes means for using artificial intelligence and a generative AI model. [Explanation of Symbols]

[1507] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of selecting a template for notifying customers of various information based on customer information obtained from a database, A means for generating customized notification content based on the aforementioned template, A means of sending the generated notification content to the customer, A system that includes this.

2. The system according to claim 1, wherein the acquired customer information includes delivery status, schedule, and activation status.

3. The system according to claim 1, wherein the means for generating notification content includes means for using artificial intelligence.

4. The system according to claim 1, wherein the notification content is in email format.

5. The system according to claim 1, comprising means for selecting the template based on conditions.

6. The system according to claim 1, wherein the means for acquiring the customer information is performed via an API.

7. The system according to claim 1, further comprising means for recording a transmission log of notification content.

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